Ping An Technology (Shenzhen) Co., LTD.

Chine

Retour au propriétaire

1-100 de 165 pour Ping An Technology (Shenzhen) Co., LTD. Trier par
Recheche Texte
Brevet
États-Unis - USPTO
Affiner par Reset Report
Date
Nouveautés (dernières 4 semaines) 1
2022 janvier (MACJ) 1
2021 décembre 1
2021 novembre 2
2021 octobre 7
Voir plus
Classe IPC
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques 35
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales 27
G06N 3/08 - Méthodes d'apprentissage 21
G06T 7/00 - Analyse d'image 19
G06N 3/04 - Architecture, p.ex. topologie d'interconnexion 18
Voir plus
Statut
En Instance 82
Enregistré / En vigueur 83
Résultats pour  brevets
  1     2        Prochaine page

1.

METHOD AND DEVICE FOR TEXT-BASED IMAGE GENERATION

      
Numéro d'application 17344484
Statut En instance
Date de dépôt 2021-06-10
Date de la première publication 2022-01-06
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Gou, Yuchuan
  • Wu, Qiancheng
  • Li, Minghao
  • Gong, Bo
  • Han, Mei

Abrégé

A method and device for image generation are provided. The method includes: obtaining a text describing a content of an image to be generated; extracting, using a text encoder, a text feature vector from the text; determining a semantic mask as spatial constraints of the image to be generated; and automatically generating the image using a generative adversarial network (GAN) model according to the semantic mask and the text feature vector.

Classes IPC  ?

  • G06T 11/00 - Génération d'images bidimensionnelles [2D]
  • G06F 40/126 - Encodage de caractères
  • G06F 40/279 - Reconnaissance d’entités textuelles
  • G06N 3/02 - Systèmes de calculateurs basés sur des modèles biologiques utilisant des modèles de réseaux neuronaux

2.

METHOD AND SYSTEM FOR RESPONDING TO VIDEO CALL SERVICE

      
Numéro d'application 16644456
Statut En instance
Date de dépôt 2018-07-27
Date de la première publication 2021-12-02
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Cheng, Huilin
  • Liu, Dechao

Abrégé

The present disclosure provides a method for responding to video call service and system, including: receiving a video call service request by the video call device; calling a video call connection process to establish a video call data transmission link with the call peer based on a communication address; locally acquiring a target file as indicated by the file transmission request, and determining a link number of the file transmission link for transmitting the target file according to the communication address and a file type of the target file, if a file transmission request sent by the call peer is received; uploading the target file to a file push server through a file uplink if the link number is not included in a local link list; and transmitting the target file to the call peer through the file transmission link corresponding to the link number.

Classes IPC  ?

  • H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
  • H04L 29/08 - Procédure de commande de la transmission, p.ex. procédure de commande du niveau de la liaison
  • H04W 24/02 - Dispositions pour optimiser l'état de fonctionnement

3.

TARGET CUSTOMER IDENTIFICATION METHOD AND DEVICE, ELECTRONIC DEVICE AND MEDIUM

      
Numéro d'application 16316028
Statut En instance
Date de dépôt 2017-09-29
Date de la première publication 2021-11-25
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Li, Fang
  • Wang, Jianming
  • Xiao, Jing

Abrégé

The present solution provides a target customer identification method and a device, an electronic device and a medium, which is applicable to the field of information processing. The method includes: obtaining personal characteristics data of potential customers; calculating a customer conversion rate of a telephone sales representative during each working time period according to the total number of customers who have made a transaction and the total number of marketing target customers of the telephone sales representative in each of working time periods; inputting the customer conversion rate of the telephone sales representative in the current working time period and the personal characteristics data of the potential customers into a pre-established random forest model to output product purchase probabilities of the potential customers; and determining a potential customer whose product purchase probability is greater than a preset threshold as a target customer of the telephone sales representative in the current working time period. In the present solution, the consideration factor of the real-time marketing capability of the telephone sales representative is added, so that the telephone sales representative can accurately find out the target customers at the current time, thereby improving customer conversion rate, marketing efficiency and target customer identification accuracy.

Classes IPC  ?

  • G06Q 30/02 - Marketing, p.ex. études et analyse de marchés, prospection, promotions, publicité, établissement du profil des acheteurs, gestion ou fidélisation de clientèle; Estimation ou détermination des prix
  • G06Q 10/06 - Ressources, gestion de tâches, gestion d'hommes ou de projets, p.ex. organisation, planification, ordonnancement ou affectation de ressources en temps, hommes ou machines; Planification dans l'entreprise; Modèles organisationnels
  • G06N 20/20 - Techniques d’ensemble en apprentissage automatique

4.

DEVICE AND METHOD FOR ALIGNMENT OF MULTI-MODAL CLINICAL IMAGES USING JOINT SYNTHESIS, SEGMENTATION, AND REGISTRATION

      
Numéro d'application 17110859
Statut En instance
Date de dépôt 2020-12-03
Date de la première publication 2021-11-25
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Liu, Fengze P.
  • Cai, Jinzheng
  • Huo, Yuankai
  • Lu, Le
  • Harrison, Adam P.

Abrégé

An image processing method for performing image alignment includes: acquiring a moving image generated by a first imaging modality; acquiring a fixed image generated by a second imaging modality; jointly optimizing a generator model, a register model, and a segmentor model applied to the moving image and the fixed image according to a plurality of cost functions; and applying a spatial transformation corresponding to the optimized register model to the moving image to align the moving image to the fixed image; wherein: the generator model generates a synthesized image from the moving image conditioned on the fixed image; the register model estimates the spatial transformation to align the synthesized image to the fixed image; and the segmentor model estimates segmentation maps of the moving image, the fixed image, and the synthesized image.

Classes IPC  ?

5.

Method And Storage Medium For Realizing Interaction Between Business Systems And At Least One Component

      
Numéro d'application 16315254
Statut En instance
Date de dépôt 2018-02-27
Date de la première publication 2021-10-28
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s) Lu, Zheng

Abrégé

A method for realizing interaction between a business system and at least one component. Steps include configuring at least one component in a frame system; displaying the frame system configured with the components on the front page of the main business system; by clicking on components displayed on the front page of the main business system, a user jumping from the main business system and logging to a front page of another business system defined by each of the clicked components.

Classes IPC  ?

  • G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
  • G06F 9/445 - Chargement ou démarrage de programme
  • G06F 8/38 - Création ou génération de code source pour la mise en œuvre d'interfaces utilisateur
  • G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p.ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comport
  • G06F 3/0482 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p.ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comport interaction avec des listes d’éléments sélectionnables, p.ex. les menus
  • G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p.ex. sélection ou manipulation d’un objet ou d’une image, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs

6.

Exclusive Agent Pool Allocation Method, Electronic Device, And Computer Readable Storage Medium

      
Numéro d'application 16315255
Statut En instance
Date de dépôt 2018-02-12
Date de la première publication 2021-10-28
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s) Niu, Hua

Abrégé

An exclusive agent pool allocation method including collecting business data of agents; grouping agents according to the business data of the agents and forming multiple exclusive agent pools; calculating business skill values of agents according to the business data of the agents and classifying priorities of the agents; of classifying priorities of agent pools according to the business data of the exclusive agent pools; and allocating calling user to the corresponding agent in the exclusive agent pool according to predetermined allocation strategy. The method solves the matching of the user and the agent in the region and the business level, allocates the agent resource according to the priority of the business skill, realizes the high match between the business skill of the agent and the business handled by the user, improves the pertinence and effectiveness of the agent service and promotes the satisfaction of the users.

Classes IPC  ?

  • H04M 3/523 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur avec répartition ou mise en file d'attente des appels
  • G06Q 10/06 - Ressources, gestion de tâches, gestion d'hommes ou de projets, p.ex. organisation, planification, ordonnancement ou affectation de ressources en temps, hommes ou machines; Planification dans l'entreprise; Modèles organisationnels
  • H04M 3/51 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur

7.

CLAIM SETTLEMENT ANTI-FRAUD METHOD, APPARATUS, DEVICE, AND STORAGE MEDIUM BASED ON GRAPH COMPUTATION TECHNOLOGY

      
Numéro d'application 17263899
Statut En instance
Date de dépôt 2019-11-12
Date de la première publication 2021-10-21
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Wang, Jianzong
  • Huang, Zhangcheng

Abrégé

A claim settlement anti-fraud method, an apparatus, a computer device, and a storage medium are provided. The method includes generating a sub-graph of doctor and patient, a sub-graph of doctor and medical advice, and a fused large graph according to medical data. A patient relationship network with several community close loops is generated by mapping the sub-graph of doctor and patient according to the fuses large graph. A similarity between any two vertexes in the patient relationship network are computed. An average similarity of each community close loop is computed. The insurance fraud actions are confirmed based on the average similarity.

Classes IPC  ?

  • G06Q 40/08 - Assurance, p.ex. analyse des risques ou pensions
  • G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
  • G16H 10/60 - TIC spécialement adaptées à la manipulation ou au traitement de données médicales ou de soins de santé relatives aux patients pour des données spécifiques de patients, p.ex. pour des dossiers électroniques de patients
  • G16H 40/20 - TIC spécialement adaptées à la gestion ou à l’administration de ressources ou d’établissements de santé; TIC spécialement adaptées à la gestion ou au fonctionnement d’équipement ou de dispositifs médicaux pour la gestion ou l’administration de ressources ou d’établissements de soins de santé, p.ex. pour la gestion du personnel hospitalier ou de salles d’opération
  • G16H 50/70 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicales; TIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour extraire des données médicales, p.ex. pour analyser les cas antérieurs d’autres patients
  • G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicales; TIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p.ex. basé sur des systèmes experts médicaux
  • G06F 16/901 - Indexation; Structures de données à cet effet; Structures de stockage
  • G06F 16/906 - Groupement; Classement

8.

SYSTEM LANGUAGE SWITCHING METHOD, READABLE STORAGE MEDIUM, TERMINAL DEVICE, AND APPARATUS

      
Numéro d'application 16328200
Statut En instance
Date de dépôt 2018-01-31
Date de la première publication 2021-10-21
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s) Cai, Jinsheng

Abrégé

The present application relates to the technical field of computers, and particularly to a system language switching method, a computer readable storage medium, a terminal device, and a device. The method includes first obtaining a preset image for setting a system language of a target terminal, then extracting text information in the image and determining a target language corresponding to the text information, and finally switching the system language of the target terminal to the target language. Through the present application, the user only needs to prepare an image for setting the system language of the target terminal in advance, for example, a piece of paper with Chinese written, and a system can obtain the text information on the image through the processes of image acquisition, text information extraction, and the like, determine that the text message is Chinese, and finally switch the system language of the target terminal to Chinese. Operations in the entire process are extremely simple and convenient, greatly improving the user experience.

Classes IPC  ?

  • G06F 40/263 - Identification de la langue
  • G06F 40/242 - Dictionnaires
  • G06T 5/00 - Amélioration ou restauration d'image
  • G06K 9/46 - Extraction d'éléments ou de caractéristiques de l'image
  • G06F 16/583 - Recherche caractérisée par l’utilisation de métadonnées, p.ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des métadonnées provenant automatiquement du contenu
  • G06K 9/32 - Alignement ou centrage du capteur d'image ou de la zone image

9.

Agent Login Method, Electronic Device And Storage Medium Based On Voiceprint Identification

      
Numéro d'application 16338957
Statut En instance
Date de dépôt 2018-02-27
Date de la première publication 2021-10-07
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s) Qiu, Bei

Abrégé

An agent login method based on voiceprint identification, which belongs to a field of login authentication. The agent login method includes receiving login request information initiated by the agent, wherein the login request information includes unique identification information identifying agent identity, verifying whether the agent is a registered agent through the unique identification information, if so, then randomly generating identity review information and providing it to the agent, and prompting the agent to read the identity review information by word-by-word prompt with color changing at constant speed, receiving voice information of the identity review information, and performing voiceprint login verification on the agent according to the received voice information. A login method with double verification of agent identity and voiceprint, and word-by-word prompt with color changing at constant speed to repeat the same, to ensure security of the login of the business system and the accuracy of the verification.

Classes IPC  ?

  • G06F 21/32 - Authentification de l’utilisateur par données biométriques, p.ex. empreintes digitales, balayages de l’iris ou empreintes vocales
  • G06F 21/36 - Authentification de l’utilisateur par représentation graphique ou iconique
  • G10L 17/06 - Techniques de prise de décision; Stratégies d’alignement de motifs
  • H04W 4/12 - Messagerie; Boîtes aux lettres; Annonces

10.

METHOD FOR SYNTHESIZING IMAGE BASED ON CONDITIONAL GENERATIVE ADVERSARIAL NETWORK AND RELATED DEVICE

      
Numéro d'application 17264312
Statut En instance
Date de dépôt 2019-11-13
Date de la première publication 2021-10-07
Propriétaire PING AN TECHNOLOGY(SHENZHEN)CO.,LTD. (Chine)
Inventeur(s)
  • Wang, Yiwen
  • Wang, Jianzong

Abrégé

A method includes: obtaining a plurality of clinical red blood cell images, dividing red blood cells of different shapes at different positions in each of the red blood cell images into a plurality of submasks, and synthesizing the submasks corresponding to each of the red blood cell images to generate one mask to obtain a plurality of masks corresponding to the red blood cell images; collecting shape data of a plurality of red blood cells from the masks to obtain a training data set, calculating a segmentation boundary of each red blood cell in the training data set, and establishing a red blood cell shape data set based on the segmentation boundary of each red blood cell; collecting distribution data of each red blood cell in the red blood cell shape data set; and synthesizing the red blood cell shape data set into a plurality of red blood cell images.

Classes IPC  ?

  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
  • G06T 7/12 - Découpage basé sur les bords
  • G06T 7/194 - Découpage; Détection de bords impliquant une segmentation premier plan-arrière-plan
  • G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
  • G06K 9/46 - Extraction d'éléments ou de caractéristiques de l'image
  • G16H 30/40 - TIC spécialement adaptées à la manipulation ou au traitement d’images médicales pour le traitement d’images médicales, p.ex. l’édition
  • G16H 10/40 - TIC spécialement adaptées à la manipulation ou au traitement de données médicales ou de soins de santé relatives aux patients pour des données relatives aux analyses de laboratoire, p.ex. pour des analyses d’échantillon de patient

11.

FACE RECOGNITION METHOD, DEVICE AND ELECTRONIC EQUIPMENT, AND COMPUTER NON-VOLATILE READABLE STORAGE MEDIUM

      
Numéro d'application 17266587
Statut En instance
Date de dépôt 2019-11-12
Date de la première publication 2021-10-07
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Zhao, Moyan
  • Wang, Hongwei

Abrégé

A face recognition method includes: detecting keypoints when receiving a first face image; acquiring a recognition score of each detectable keypoint and serial numbers of missing keypoints; acquiring a plurality of target keypoints in the plurality of detectable keypoints having a predetermined face feature association relationship with the missing keypoints when the influence score is higher than a predetermined score threshold; acquiring a target face feature template having a degree of position combination with the plurality of target keypoints greater than a predetermined combination degree threshold; and stitching the target face feature template and the plurality of target keypoints on the first face image to obtain a second face image so as to detect all the keypoints according to the second face image for performing the face recognition.

Classes IPC  ?

  • G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques

12.

SYSTEMS AND METHODS FOR TUMOR CHARACTERIZATION

      
Numéro d'application 16836855
Statut En instance
Date de dépôt 2020-03-31
Date de la première publication 2021-09-30
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Harrison, Adam P.
  • Huo, Yuankai
  • Cai, Jinzheng
  • Raju, Ashwin
  • Yan, Ke
  • Lu, Le

Abrégé

Systems and methods for characterizing a region of interest (ROI) in a medical image are provided. An exemplary system may include a memory storing instructions and at least one processor communicatively coupled to the memory to execute the instructions which, when executed by the processor, may cause the processor to perform operations. The operations may include detecting one or more candidate ROIs from the medical image using a three-dimensional (3D) machine learning network. The operations may also include determining a key slice for each candidate ROI. The operations may further include selecting a primary ROI from the one or more candidate ROIs based on the respective key slices. In addition, the operations may include classifying the primary ROI into one of a plurality of categories using a texture-based classifier based on the key slice corresponding to the primary ROI.

Classes IPC  ?

  • G06T 7/00 - Analyse d'image
  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
  • G06T 7/49 - Analyse de la texture basée sur la description de texture structurelle, p.ex. en utilisant des primitives ou des règles de placement
  • A61B 6/00 - Appareils pour diagnostic par radiations, p.ex. combinés avec un équipement de thérapie par radiations
  • A61B 6/03 - Tomographes assistés par ordinateur

13.

LONG SHORT-TERM MEMORY MODEL-BASED DISEASE PREDICTION METHOD AND APPARATUS, AND COMPUTER DEVICE

      
Numéro d'application 17264299
Statut En instance
Date de dépôt 2019-08-30
Date de la première publication 2021-09-23
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Jia, Wenxiao
  • Tan, Kewei
  • Li, Xiang
  • Xie, Guotong

Abrégé

A long short-term memory (LSTM) model-based disease prediction method and apparatus, a computer device, and a storage medium are provided. The method includes: obtaining first medical data of a target object and second medical data of an associated object; inputting the first medical data and the second medical data into a first LSTM network in the LSTM model, to obtain a hidden state vector sequence in the first LSTM network; inputting the hidden state vector sequence into a second LSTM network for operation, to obtain a disease prediction result; selecting a predicted disease with an incidence rate higher than a preset threshold, and recording the predicted disease as a designated disease, and obtaining, based on a preset disease association network, an associated disease directly connected to the designated disease; and outputting the disease prediction result and the associated disease, thereby improving the prediction accuracy.

Classes IPC  ?

  • G16H 50/50 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicales; TIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour la simulation ou la modélisation des troubles médicaux

14.

NEURAL NETWORK MODEL TRAINING METHOD AND APPARATUS, COMPUTER DEVICE, AND STORAGE MEDIUM

      
Numéro d'application 17264307
Statut En instance
Date de dépôt 2019-05-30
Date de la première publication 2021-09-23
Propriétaire PING AN TECHNOLOGY(SHENZHEN)CO.,LTD. (Chine)
Inventeur(s)
  • Guo, Yan
  • Lv, Bin
  • Lv, Chuanfeng
  • Xie, Guotong

Abrégé

A neural network model training method and apparatus, a computer device, and a storage medium are provided. The method includes: obtaining a model prediction value of each of all reference samples based on a trained deep neural network model, calculating a difference measurement index between the model prediction value of each reference sample and a real annotation corresponding to the reference sample, and using a target reference sample whose difference measurement index is less than or equal to a preset threshold as a comparison sample; using a training sample whose similarity with the comparison sample meets a preset augmentation condition as a to-be-augmented sample; and performing data augmentation on the to-be-augmented sample, and using the obtained target training sample as a training sample to train the trained deep neural network model until model prediction values of all verification samples in a verification set meet a preset training ending condition.

Classes IPC  ?

  • G06N 3/08 - Méthodes d'apprentissage
  • G06N 3/04 - Architecture, p.ex. topologie d'interconnexion

15.

DATA STORAGE METHOD AND APPARATUS, STORAGE MEDIUM AND COMPUTER DEVICE

      
Numéro d'application 17264321
Statut En instance
Date de dépôt 2018-10-21
Date de la première publication 2021-09-23
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Sun, Cheng
  • Ye, Junfeng
  • Lai, Yunhui
  • Luo, Xianxian
  • Long, Juegang

Abrégé

A data storage method includes: acquiring target data to be stored, and classifying refresh rates of the target data to be stored according to a front-end system; subjecting the target data to be stored with high refresh rates as classified and the target data to be stored with low refresh rates as classified to a Hash calculation to obtain a first type Hash value and a second type Hash value; determining storage data segments corresponding to the first type Hash value and the second type Hash value according to a preset storage data segment determination relationship, and storing the target data to be stored with high refresh rates and the target data to be stored with low refresh rates into the storage data segments corresponding to the first type Hash value and the second type Hash value, respectively.

Classes IPC  ?

  • G06F 3/06 - Entrée numérique à partir de, ou sortie numérique vers des supports d'enregistrement

16.

METHOD, DEVICE, EQUIPMENT AND STORAGE MEDIUM FOR LOCATING TRACKED TARGETS

      
Numéro d'application 17266187
Statut En instance
Date de dépôt 2018-12-24
Date de la première publication 2021-09-23
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s) Yang, Guoqing

Abrégé

A method for tracking a target includes: acquiring original position information of an original target point selected by a user contained in a locating request if the locating request for tracking a target is received; carrying out target prediction on a current frame image according to a preset target prediction model to obtain a target prediction result; calculating an Euclidean distance between each of the targets to be tracked and the original target point according to the target position information and original coordinates of each of the target regions to obtain N distances; selecting a distance with the smallest numerical value from the N distances as a target distance, acquiring target position information corresponding to the target distance, and determining a target to be tracked in a target region corresponding to the obtained target position information as a tracked target corresponding to an original target point.

Classes IPC  ?

  • G06T 7/246 - Analyse du mouvement utilisant des procédés basés sur les caractéristiques, p.ex. le suivi des coins ou des segments
  • G06T 7/70 - Détermination de la position ou de l'orientation des objets ou des caméras
  • G06N 3/08 - Méthodes d'apprentissage

17.

ACTUARIAL PROCESSING METHOD AND DEVICE

      
Numéro d'application 16321809
Statut En instance
Date de dépôt 2018-01-31
Date de la première publication 2021-09-16
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Liu, Yongfan
  • Li, Zhi

Abrégé

An embodiment of the present application discloses an actuarial processing method for solving the problems that the actuarial processing takes a long time and the processing efficiency is low. The method according to the embodiment of the present application includes determining target policy data to be actuarially processed; grouping the target policy data according to a preset product grouping rule to obtain each data group; extracting data dimensions in the data group that meet preset conditions; splicing data values belonging to the same data dimension in the data group to obtain a spliced string; encrypting the obtained spliced string to obtain a dimension identifier corresponding to the data dimension in the data group; grouping the target policy data under the data group according to the dimension identifier corresponding to each of the data dimensions extracted from the data group, to obtain each data subgroup to be actuarially processed under the data group; and performing actuarial processing respectively on each of the data subgroups to be actuarially processed by a preset actuarial program. An embodiment of the present application also provides an actuarial processing device.

Classes IPC  ?

  • G06Q 40/08 - Assurance, p.ex. analyse des risques ou pensions
  • G06F 16/242 - Formulation des requêtes
  • H04L 9/06 - Dispositions pour les communications secrètes ou protégées l'appareil de chiffrement utilisant des registres à décalage ou des mémoires pour le codage par blocs, p.ex. système DES

18.

METHOD AND SYSTEM FOR IMAGE SEGMENTATION

      
Numéro d'application 17128993
Statut En instance
Date de dépôt 2020-12-21
Date de la première publication 2021-09-16
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Zheng, Kang
  • Lu, Yuhang
  • Li, Weijian
  • Wang, Yirui
  • Harrison, Adam P
  • Lu, Le
  • Miao, Shun

Abrégé

An image segmentation method includes generating a CTN (contour transformer network) model for image segmentation, where generating the CTN model includes providing an annotated image, the annotated image including an annotated contour, providing a plurality of unannotated images, pairing the annotated image to each of the plurality of unannotated images to obtain a plurality of image pairs, feeding the plurality of image pairs to an image encoder to obtain a plurality of first-processed image pairs, and feeding the plurality of first-processed image pairs to a contour tuner to obtain a plurality of second-processed image pairs.

Classes IPC  ?

19.

METHOD AND COMPUTER READABLE STORAGE MEDIUM FOR AGENT MATCHING IN REMOTE INTERVIEW SIGNATURE

      
Numéro d'application 16466284
Statut En instance
Date de dépôt 2018-02-27
Date de la première publication 2021-09-09
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s) Niu, Hua

Abrégé

The present disclosure discloses a remote interview signature agent matching method, an electronic device and a computer memory readable storage medium, said method comprising the following steps: Step 01, an user end inquiring whether there is an interview signature task, if so, then going to Step 02, otherwise ending the method; Step 02, the user end sending an interview signature request to an agent end, wherein the interview signature request includes user information and business information, the agent end confirming the user information and the business information; Step 03, the agent end allocating the interview signature request to a matching agent according to preset allocation strategy; Step 04, the matching agent performing matching check of user information and business information on the interview signature request, if matching is successful, connecting to incoming call user, otherwise returning to Step 03 for reallocation.

Classes IPC  ?

  • G06Q 10/06 - Ressources, gestion de tâches, gestion d'hommes ou de projets, p.ex. organisation, planification, ordonnancement ou affectation de ressources en temps, hommes ou machines; Planification dans l'entreprise; Modèles organisationnels
  • H04M 3/523 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur avec répartition ou mise en file d'attente des appels

20.

TRAFFIC DATA SELF-RECOVERY PROCESSING METHOD, READABLE STORAGE MEDIUM, SERVER AND APPARATUS

      
Numéro d'application 16095344
Statut En instance
Date de dépôt 2018-02-26
Date de la première publication 2021-09-02
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Yu, Liangling
  • Dai, Congjian
  • Fang, Huangwei
  • Ye, Weiwei
  • Li, Xiaohua

Abrégé

Embodiments of the present application disclose a traffic data self-recovery processing method, including: monitoring an operation result of traffic data synchronization operation of a target system; repeatedly performing the traffic data synchronization operation of the target system until the traffic data synchronization is successful or cumulative number of traffic data synchronization failures exceed a failure frequency threshold, if the monitored operation result is that the traffic data synchronization is failed; clearing the cumulative number if the monitored operation result is that the traffic data synchronization is successful; stopping the traffic data synchronization operation of the target system and sending out a message indicative of the traffic data synchronization failure if the cumulative number of traffic data synchronization failures exceeds the failure frequency threshold, wherein the failure frequency threshold is determined by current network signal intensity of the target system and is in a positive correlation with current network signal intensity. The embodiments of the present application further provide a server for traffic data self-recovery processing.

Classes IPC  ?

  • G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p.ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
  • H04L 12/26 - Dispositions de surveillance; Dispositions de test

21.

Method, apparatus, computer device and storage medium of page displaying

      
Numéro d'application 16097872
Numéro de brevet 11163851
Statut Délivré - en vigueur
Date de dépôt 2017-11-23
Date de la première publication 2021-08-19
Date d'octroi 2021-11-02
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s) Shi, Guiling

Abrégé

A method of page displaying includes: obtaining page data of a current page of an application; the page data includes a screenshot and view identifiers and view names of a plurality of views; adding the plurality of view identifiers to a plurality of arrays having different levels according to a preset rule; building a multi-fork tree corresponding to the current page of the application using the array; generating hierarchical paths corresponding to the plurality of views according to the multi-fork tree, adding corresponding burial point frames to the corresponding views according to the hierarchical path, and transmitting the screenshot provided with burial point frames to the preset terminal, so that the preset terminal displays the screenshot with burial point frames.

Classes IPC  ?

  • G06F 17/00 - TRAITEMENT ÉLECTRIQUE DE DONNÉES NUMÉRIQUES Équipement ou méthodes de traitement de données ou de calcul numérique, spécialement adaptés à des fonctions spécifiques
  • G06F 16/958 - Organisation ou gestion de contenu de sites Web, p.ex. publication, conservation de pages ou liens automatiques
  • G06F 16/901 - Indexation; Structures de données à cet effet; Structures de stockage
  • G06F 16/903 - Requêtes
  • G06F 16/957 - Optimisation de la navigation, p.ex. mise en cache ou distillation de contenus

22.

CO-HETEROGENEOUS AND ADAPTIVE 3D PATHOLOGICAL ABDOMINAL ORGAN SEGMENTATION USING MULTI-SOURCE AND MULTI-PHASE CLINICAL IMAGE DATASETS

      
Numéro d'application 17089257
Statut En instance
Date de dépôt 2020-11-04
Date de la première publication 2021-08-19
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Harrison, Adam P.
  • Raju, Ashwin
  • Huo, Yuankai
  • Cai, Jinzheng
  • Lu, Le

Abrégé

The present disclosure describes a computer-implemented method for processing clinical three-dimensional image. The method includes training a fully supervised segmentation model using a labelled image dataset containing images for a disease at a predefined set of contrast phases or modalities, allow the segmentation model to segment images at the predefined set of contrast phases or modalities; finetuning the fully supervised segmentation model through co-heterogenous training and adversarial domain adaptation (ADA) using an unlabelled image dataset containing clinical multi-phase or multi-modality image data, to allow the segmentation model to segment images at contrast phases or modalities other than the predefined set of contrast phases or modalities; and further finetuning the fully supervised segmentation model using domain-specific pseudo labelling to identify pathological regions missed by the segmentation model.

Classes IPC  ?

  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
  • G06T 7/00 - Analyse d'image
  • G06T 7/11 - Découpage basé sur les zones
  • G06K 9/46 - Extraction d'éléments ou de caractéristiques de l'image
  • G16H 30/40 - TIC spécialement adaptées à la manipulation ou au traitement d’images médicales pour le traitement d’images médicales, p.ex. l’édition

23.

MACHINE LEARNING BASED MEDICAL DATA CLASSIFICATION METHOD, COMPUTER DEVICE, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM

      
Numéro d'application 17165665
Statut En instance
Date de dépôt 2021-02-02
Date de la première publication 2021-08-19
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Chen, Xianxian
  • Ruan, Xiaowen
  • Xu, Liang

Abrégé

A machine learning based medical data classification method is provided. The method includes: a medical data classification request including medical record information is received; a preset medical term base is obtained, and word segmentation is performed on the medical record information according to medical terms in the medical term base to obtain multiple text vectors; features of the multiple text vectors are extracted to obtain multiple text vectors and corresponding feature dimension values; a target classifier is trained with multiple pieces of medical data, and the multiple text vectors and the corresponding feature dimension values are traversed and calculated; until a target node corresponding to the multiple text vectors is traversed, class probabilities corresponding to the multiple text vectors are calculated according to the target node, and a class result corresponding to the medical record information is obtained according to the class probabilities and is pushed to a terminal.

Classes IPC  ?

  • G16H 10/60 - TIC spécialement adaptées à la manipulation ou au traitement de données médicales ou de soins de santé relatives aux patients pour des données spécifiques de patients, p.ex. pour des dossiers électroniques de patients
  • G06N 20/00 - Apprentissage automatique
  • G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicales; TIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p.ex. basé sur des systèmes experts médicaux
  • G16H 70/20 - TIC spécialement adaptées à la manipulation ou au traitement de références médicales concernant des pratiques ou des directives
  • G16H 50/70 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicales; TIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour extraire des données médicales, p.ex. pour analyser les cas antérieurs d’autres patients
  • G06F 40/30 - Analyse sémantique
  • G06F 40/284 - Analyse lexicale, p.ex. segmentation en unités ou cooccurrence

24.

METHOD FOR CONDUCTING STATISTICS ON INSURANCE TYPE STATE INFORMATION OF POLICY, TERMINAL DEVICE AND STORAGE MEDIUM

      
Numéro d'application 16301429
Statut En instance
Date de dépôt 2018-02-12
Date de la première publication 2021-07-29
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s) Wang, Haiping

Abrégé

The present application is applicable to the technical field of insurance type information processing, and provides a method for conducting statistics on insurance type state information of a policy, a terminal device, and a storage medium. The method includes receiving a unique identifier of an insurance type of a policy; searching for, in a log table, all state change records corresponding to the unique identifier of the insurance type of the policy; sorting all the found state change records in chronological order; determining whether two adjacent state change records are the same; when the two adjacent state change records are different, subtracting the time point of the previous state from the time point of the latter state change record to obtain a time interval; and determining the duration of a valid state based on the time interval. Through the above method, the data processing efficiency can be greatly improved.

Classes IPC  ?

  • G06Q 10/10 - Bureautique, p.ex. gestion informatisée de courrier électronique ou logiciels de groupe; Gestion du temps, p.ex. calendriers, rappels, décompte de réunions ou de temps
  • G06Q 30/00 - Commerce, p.ex. achat ou vente, ou commerce électronique
  • G06F 16/22 - Indexation; Structures de données à cet effet; Structures de stockage
  • G06F 16/23 - Mise à jour
  • G06F 16/245 - Traitement des requêtes
  • G06F 7/08 - Tri, c. à d. rangement des supports d'enregistrement dans un ordre de succession numérique ou autre, selon la classification d'au moins certaines informations portées sur les supports

25.

DEVICE AND METHOD FOR DETECTING CLINICALLY IMPORTANT OBJECTS IN MEDICAL IMAGES WITH DISTANCE-BASED DECISION STRATIFICATION

      
Numéro d'application 17094984
Statut En instance
Date de dépôt 2020-11-11
Date de la première publication 2021-07-29
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Yan, Ke P.
  • Zhu, Zhuotun
  • Jin, Dakai
  • Cai, Jinzheng
  • Harrison, Adam P.
  • Guo, Dazhou
  • Lu, Le

Abrégé

A method for performing a computer-aided diagnosis (CAD) includes: acquiring a medical image set; generating a three-dimensional (3D) tumor distance map corresponding to the medical image set, each voxel of the tumor distance map representing a distance from the voxel to a nearest boundary of a primary tumor present in the medical image set; and performing neural-network processing of the medical image set to generate a predicted probability map to predict presence and locations of oncology significant lymph nodes (OSLNs) in the medical image set, wherein voxels in the medical image set are stratified and processed according to the tumor distance map.

Classes IPC  ?

  • G06T 7/00 - Analyse d'image
  • G06T 7/70 - Détermination de la position ou de l'orientation des objets ou des caméras
  • G06T 11/00 - Génération d'images bidimensionnelles [2D]
  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
  • G06K 9/46 - Extraction d'éléments ou de caractéristiques de l'image
  • G06T 9/00 - Codage d'image
  • A61B 6/03 - Tomographes assistés par ordinateur
  • A61B 6/00 - Appareils pour diagnostic par radiations, p.ex. combinés avec un équipement de thérapie par radiations
  • G06N 3/08 - Méthodes d'apprentissage
  • G16H 30/40 - TIC spécialement adaptées à la manipulation ou au traitement d’images médicales pour le traitement d’images médicales, p.ex. l’édition
  • G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicales; TIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p.ex. basé sur des systèmes experts médicaux

26.

DATA NOISE REDUCTION METHOD, DEVICE, COMPUTER APPARATUS AND STORAGE MEDIUM

      
Numéro d'application 16634438
Statut En instance
Date de dépôt 2018-12-24
Date de la première publication 2021-07-29
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Yu, Xiuming
  • Wang, Wei
  • Xiao, Jing

Abrégé

A data noise reduction method based on data resource. The method includes: acquiring a corresponding characteristic combination according to a received request for noise reduction; acquiring corresponding initial data according to the characteristic combination; calculating a discrimination degree of the characteristic combination; screening the discrimination degree of the characteristic combination using a preset initial discrimination degree threshold, and acquiring a characteristic combination corresponding to the discrimination degree that meets a preset requirement; generating an initial characteristic combination according to the corresponding characteristic combination; extracting an available characteristic combination from the initial characteristic combination according to a preset evaluation index; performing a noise reduction process to the initial data according to the available characteristic combination, deleting noise data from the initial data and acquires available data, and sending the available data to the terminal.

Classes IPC  ?

  • G06F 16/215 - Amélioration de la qualité des données; Nettoyage des données, p.ex. déduplication, suppression des entrées non valides ou correction des erreurs typographiques
  • G06F 16/23 - Mise à jour
  • G06F 16/22 - Indexation; Structures de données à cet effet; Structures de stockage
  • G06F 16/28 - Bases de données caractérisées par leurs modèles, p.ex. des modèles relationnels ou objet
  • G06F 11/34 - Enregistrement ou évaluation statistique de l'activité du calculateur, p.ex. des interruptions ou des opérations d'entrée–sortie

27.

SERVICE LINE-BASED PREDICATION METHOD, DEVICE, STORAGE MEDIUM AND TERMINAL

      
Numéro d'application 16093628
Statut En instance
Date de dépôt 2018-02-27
Date de la première publication 2021-07-22
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s) Wan, Xiaohui

Abrégé

A service line-based predication method and device, a storage medium and a terminal are provided. The method includes: when service predication is performed on a specified service line, acquiring a predication model corresponding to this specified service line, and input dimensions and output dimensions of this predication; acquiring predication data satisfying the input dimensions from a data warehouse; performing trend analysis on the predication data adopting Monte Carlo simulation and geometric Brownian motion through the predication model to obtain the predication values of the output dimensions; and calculating total task amount and manpower quantity required to be input of the specified service line within a specified period of time according to the predication values. The predication model is divided into an incoming call predication model and a calling predication model according to service types. The present disclosure realizes that different predication modes are adopted aiming at different service scenes.

Classes IPC  ?

  • G06F 30/20 - Optimisation, vérification ou simulation de l’objet conçu
  • G06F 16/28 - Bases de données caractérisées par leurs modèles, p.ex. des modèles relationnels ou objet
  • G06Q 10/06 - Ressources, gestion de tâches, gestion d'hommes ou de projets, p.ex. organisation, planification, ordonnancement ou affectation de ressources en temps, hommes ou machines; Planification dans l'entreprise; Modèles organisationnels

28.

METHOD FOR CREATING UNDERWRITING DECISION TREE, COMPUTER DEVICE AND STORAGE MEDIUM

      
Numéro d'application 16096011
Statut En instance
Date de dépôt 2017-09-29
Date de la première publication 2021-07-22
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Shao, Zhengbo
  • Li, Bin
  • Chen, Jie
  • Gao, Xue
  • Ma, Xiangdong
  • Ding, Jie
  • Zhang, Jie

Abrégé

A method for creating an underwriting decision tree includes: acquiring a sample training set including different sample attributes; calculating an entropy value gain that represents an effect of an attribute on an underwriting result of each attribute, according to the underwriting result of a sample of each attribute in the sample training set; taking the attribute with a highest entropy value gain as a current node of the underwriting decision tree, and dividing a sub-attribute corresponding to the attribute with the highest entropy value gain as a next node of the current node; extracting a divided sample training subset of the sub-attribute from the sample training set; determining the sample training subset as the sample training set, and calculating the entropy value gain of the sub-attribute recursively and dividing the sub-attribute till the divided sub-attribute of the next node satisfies a preset condition of becoming a leaf node of the underwriting decision tree.

Classes IPC  ?

  • G06Q 10/10 - Bureautique, p.ex. gestion informatisée de courrier électronique ou logiciels de groupe; Gestion du temps, p.ex. calendriers, rappels, décompte de réunions ou de temps
  • G06Q 40/08 - Assurance, p.ex. analyse des risques ou pensions
  • G06N 5/00 - Systèmes de calculateurs utilisant des modèles basés sur la connaissance
  • G06N 20/00 - Apprentissage automatique

29.

METHOD, DEVICE, USER TERMINAL AND STORAGE MEDIUM OF QUERYING STATUS OF ELECTRONIC POLICY

      
Numéro d'application 16097992
Statut En instance
Date de dépôt 2018-02-26
Date de la première publication 2021-07-22
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Zhang, Jie
  • Gao, Xue
  • Li, Bin
  • Chen, Jie
  • Shao, Zhengbo
  • Ma, Xiangdong
  • Ding, Jie

Abrégé

A method of querying a status of an electronic insurance policy includes: receiving an inputted policy number; querying an initial status and an operation flow set of the electronic insurance policy corresponding to the policy number when the policy number is a valid policy number; obtaining a mapped status subset according to a status total set to which the initial status belongs and a status that each operation flow in the operation flow set is mapped in the status total set; and displaying the initial status of the electronic insurance policy and the obtained status subset.

Classes IPC  ?

  • G06Q 10/10 - Bureautique, p.ex. gestion informatisée de courrier électronique ou logiciels de groupe; Gestion du temps, p.ex. calendriers, rappels, décompte de réunions ou de temps
  • G06F 16/245 - Traitement des requêtes
  • G06F 16/248 - Présentation des résultats de requêtes
  • G06Q 40/08 - Assurance, p.ex. analyse des risques ou pensions
  • G06Q 30/00 - Commerce, p.ex. achat ou vente, ou commerce électronique

30.

METHOD AND APPARATUS FOR PREDICTING CUSTOMER PURCHASE INTENTION, ELECTRONIC DEVICE AND MEDIUM

      
Numéro d'application 16099425
Statut En instance
Date de dépôt 2018-01-31
Date de la première publication 2021-07-22
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Li, Fang
  • Wang, Jianming
  • Xiao, Jing

Abrégé

The present solution provides a method and apparatus for predicting a customer purchase intention, an electronic device and a medium, which is applicable to the field of information processing. The method includes: obtaining personal characteristics data of a customer; inputting the personal characteristic data into a pre-established random forest model, to output an objective purchase tendency value of the customer; obtaining a subjective purchase tendency value of the customer according to an emotional tendency of the customer in a historical telemarketing process; weighting the objective purchase tendency value and the subjective purchase tendency value, and outputting the weighted result as an actual purchase tendency degree of the customer; and determining the customer whose actual purchase tendency degree is greater than a preset threshold as a potential customer, so that a telephone sales person makes a telephone call back to the potential customer and market a telemarketed product. According to the present solution, the potential customer is determined by integrating multi-aspect consideration factors, and therefore the forecast accuracy of the potential customer is improved; by weighting the objective purchase tendency value and the subjective purchase tendency value, the quantitative calculation of the customer purchase intention is achieved.

Classes IPC  ?

  • G06Q 30/02 - Marketing, p.ex. études et analyse de marchés, prospection, promotions, publicité, établissement du profil des acheteurs, gestion ou fidélisation de clientèle; Estimation ou détermination des prix
  • G06Q 10/06 - Ressources, gestion de tâches, gestion d'hommes ou de projets, p.ex. organisation, planification, ordonnancement ou affectation de ressources en temps, hommes ou machines; Planification dans l'entreprise; Modèles organisationnels
  • G06N 20/20 - Techniques d’ensemble en apprentissage automatique
  • G06N 5/00 - Systèmes de calculateurs utilisant des modèles basés sur la connaissance
  • G06N 5/04 - Méthodes ou dispositifs inférents
  • G06F 40/30 - Analyse sémantique
  • H04M 3/523 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur avec répartition ou mise en file d'attente des appels

31.

USER PERMISSION DATA QUERY METHOD AND APPARATUS, ELECTRONIC DEVICE AND MEDIUM

      
Numéro d'application 16099672
Statut En instance
Date de dépôt 2017-09-29
Date de la première publication 2021-07-22
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Dong, Chao
  • Chen, Yaozhang
  • Song, Junfei
  • He, Yongjia

Abrégé

The present solution is applicable to the technical field of data management, and provides a user permission data query method and device, an electronic device and a medium. The method includes the steps of: obtaining a first data table including staff identification numbers and departments corresponding to the staff identification numbers, and obtaining a second data table including a correspondence relationship among the staff identification numbers, roles, and administration authority information; obtaining, from the second data table, a plurality of data records having the same staff identification number and the same role, calculating an MD5 value corresponding to the staff identification number and the role, and then storing a correspondence relationship among the staff identification number, the role, and the MD5 value in a third data table; screening various MD5 values that are different from each other, and obtaining the management departments and the management staffs respectively corresponding to the various MD5 values based on the associated data tables; obtaining a MD5 value corresponding to the permission query request and determining the management departments and the management staffs corresponding to the MD5 value as permission data of a user, when a permission query request is received. The present solution has greatly improved the performance of a system and query efficiency of the permission data.

Classes IPC  ?

  • G06F 21/62 - Protection de l’accès à des données via une plate-forme, p.ex. par clés ou règles de contrôle de l’accès
  • G06F 21/60 - Protection de données
  • G06F 16/2455 - Exécution des requêtes
  • G06F 16/248 - Présentation des résultats de requêtes
  • G06F 16/22 - Indexation; Structures de données à cet effet; Structures de stockage
  • G06F 16/28 - Bases de données caractérisées par leurs modèles, p.ex. des modèles relationnels ou objet

32.

METHOD AND SYSTEM FOR HARVESTING LESION ANNOTATIONS

      
Numéro d'application 16984727
Statut En instance
Date de dépôt 2020-08-04
Date de la première publication 2021-07-22
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Cai, Jinzheng
  • Harrison, Adam P.
  • Yan, Ke
  • Huo, Yuankai
  • Lu, Le

Abrégé

A method of harvesting lesion annotations includes conditioning a lesion proposal generator (LPG) based on a first two-dimensional (2D) image set to obtain a conditioned LPG, including adding lesion annotations to the first 2D image set to obtain a revised first 2D image set, forming a three-dimensional (3D) composite image according to the revised first 2D image set, reducing false-positive lesion annotations from the revised first 2D image set according to the 3D composite image to obtain a second-revised first 2D image set, and feeding the second-revised first 2D image set to the LPG to obtain the conditioned LPG, and applying the conditioned LPG to a second 2D image set different than the first 2D image set to harvest lesion annotations.

Classes IPC  ?

  • G06T 7/00 - Analyse d'image
  • G06T 5/50 - Amélioration ou restauration d'image en utilisant plusieurs images, p.ex. moyenne, soustraction
  • G06T 19/20 - Manipulation de modèles ou d'images tridimensionnels [3D] pour infographie Édition d'images tridimensionnelles [3D], p.ex. modification de formes ou de couleurs, alignement d'objets ou positionnements de parties

33.

METHOD AND DEVICE FOR STRATIFIED IMAGE SEGMENTATION

      
Numéro d'application 16928521
Statut En instance
Date de dépôt 2020-07-14
Date de la première publication 2021-07-22
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Guo, Dazhou
  • Jin, Dakai
  • Zhu, Zhuotun
  • Harrison, Adam P
  • Lu, Le

Abrégé

A method and device for stratified image segmentation are provided. The method includes: obtaining a three-dimensional (3D) image data set representative of a region comprising at least three levels of objects; generating a first segmentation result indicating boundaries of anchor-level objects in the region based on a first neural network (NN) model corresponding to the anchor-level objects; generating a second segmentation result indicating boundaries of mid-level objects in the region based on the first segmentation result and a second NN model corresponding to the mid-level objects; and generating a third segmentation result indicating small-level objects in the region based on the first segmentation result, a third NN model corresponding to the small-level objects, and cropped regions corresponding to the small-level objects.

Classes IPC  ?

  • G06T 7/11 - Découpage basé sur les zones
  • G06T 7/00 - Analyse d'image
  • G06N 3/04 - Architecture, p.ex. topologie d'interconnexion
  • G06T 17/00 - Modélisation tridimensionnelle [3D] pour infographie

34.

Topic monitoring for early warning with extended keyword similarity

      
Numéro d'application 16090351
Numéro de brevet 11205046
Statut Délivré - en vigueur
Date de dépôt 2017-06-28
Date de la première publication 2021-07-22
Date d'octroi 2021-12-21
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Wang, Jianzong
  • Huang, Zhangcheng
  • Wu, Tianbo
  • Xiao, Jing

Abrégé

A method for topic early warning includes: acquiring a self-defined keyword; calculating similarity between the self-defined keyword and each word in a corpus, and acquiring extended keywords related to the self-defined keyword from the corpus according to the similarity; selecting a target keyword from the extended keywords according to a type of the extended keywords and similarity between the extended keywords and the self-defined keyword, and adding the target keyword to a target keyword list; performing real-time monitoring according to the target keyword in the target keyword list; and performing topic early warning when it is monitored that the number of topics corresponding to the target keyword reaches a preset threshold.

Classes IPC  ?

35.

Deep learning based license plate identification method, device, equipment, and storage medium

      
Numéro d'application 16097291
Numéro de brevet 11164027
Statut Délivré - en vigueur
Date de dépôt 2017-08-31
Date de la première publication 2021-07-22
Date d'octroi 2021-11-02
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Wang, Jianzong
  • Ma, Jin
  • Huang, Zhangcheng
  • Wu, Tianbo
  • Xiao, Jing

Abrégé

A deep learning based license plate identification method, device, equipment, and storage medium. The deep learning based license plate identification method comprises: extracting features of an original captured image by using a single shot multi-box detector to obtain a target license plate image; correcting the target license plate image to obtain a corrected license plate image; identifying the corrected license plate image by using a bi-directional long short-term memory model to obtain target license plate information. When the deep learning based license plate identification method performs license plate identification, the identification efficiency is high and the accuracy is higher.

Classes IPC  ?

  • G06K 9/32 - Alignement ou centrage du capteur d'image ou de la zone image
  • G06K 9/46 - Extraction d'éléments ou de caractéristiques de l'image
  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
  • G06N 3/08 - Méthodes d'apprentissage

36.

Website vulnerability scan method, device, computer apparatus, and storage medium

      
Numéro d'application 16097693
Numéro de brevet 11190536
Statut Délivré - en vigueur
Date de dépôt 2017-10-30
Date de la première publication 2021-07-22
Date d'octroi 2021-11-30
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s) He, Shuangning

Abrégé

A method of scanning website vulnerability comprising: reading a vulnerability scan task in a scan task pool; finding a website corresponding to the vulnerability scan task, acquiring access data of the website, and obtaining a popularity coefficient of the website according to the access data; acquiring historical vulnerability scan data and a vulnerability risk level table, and obtaining a security risk coefficient of the vulnerability scan task according to the historical vulnerability scan data and the vulnerability risk level table; acquiring update time data of the vulnerability scan task, and calculating a time coefficient of the vulnerability scan task according to the update time data; inputting the popularity coefficient, the security risk coefficient, and the time coefficient into a preset priority evaluation model for processing, and obtaining an execution priority weight of the vulnerability scan task; and executing vulnerability scan tasks in the scan task pool in descending order according to the execution priority weights.

Classes IPC  ?

  • H04L 29/00 - Dispositions, appareils, circuits ou systèmes non couverts par un seul des groupes
  • H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole

37.

METHOD, DEVICE, COMPUTER APPARATUS, AND STORAGE MEDIUM FOR STORING DATA

      
Numéro d'application 16097783
Statut En instance
Date de dépôt 2017-10-31
Date de la première publication 2021-07-22
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO. LTD. (Chine)
Inventeur(s) Zhong, Wenqin

Abrégé

A method of storing data, a device, a computer apparatus, and a storage medium relate to data processing technical field. The method of storing data comprising: acquiring call data obtained in a unit time period; preprocessing the call data based on a preset processing rule according to information carried by the call data; and storing a pre-processed call data, a start time and an end time of the unit time period simultaneously.

Classes IPC  ?

  • G06F 16/2458 - Types spéciaux de requêtes, p.ex. requêtes statistiques, requêtes floues ou requêtes distribuées
  • G06F 7/16 - Interclassement et tri conjugués
  • G06F 16/248 - Présentation des résultats de requêtes

38.

DEVICE AND METHOD FOR UNIVERSAL LESION DETECTION IN MEDICAL IMAGES

      
Numéro d'application 16983373
Statut En instance
Date de dépôt 2020-08-03
Date de la première publication 2021-07-22
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Yan, Ke
  • Cai, Jinzheng
  • Harrison, Adam P.
  • Jin, Dakai
  • Lu, Le

Abrégé

A method for performing a computer-aided diagnosis (CAD) for universal lesion detection includes: receiving a medical image; processing the medical image to predict lesion proposals and generating cropped feature maps corresponding to the lesion proposals; for each lesion proposal, applying a plurality of lesion detection classifiers to generate a plurality of lesion detection scores, the plurality of lesion detection classifiers including a whole-body classifier and one or more organ-specific classifiers; for each lesion proposal, applying an organ-gating classifier to generate a plurality of weighting coefficients corresponding to the plurality of lesion detection classifiers; and for each lesion proposal, performing weight gating on the plurality of lesion detection scores with the plurality of weighting coefficients to generate a comprehensive lesion detection score.

Classes IPC  ?

  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
  • G06T 7/00 - Analyse d'image
  • G06K 9/32 - Alignement ou centrage du capteur d'image ou de la zone image
  • G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicales; TIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p.ex. basé sur des systèmes experts médicaux
  • G16H 30/40 - TIC spécialement adaptées à la manipulation ou au traitement d’images médicales pour le traitement d’images médicales, p.ex. l’édition
  • G06N 3/08 - Méthodes d'apprentissage
  • G06N 3/04 - Architecture, p.ex. topologie d'interconnexion

39.

ESTIMATING BONE MINERAL DENSITY FROM PLAIN RADIOGRAPH BY ASSESSING BONE TEXTURE WITH DEEP LEARNING

      
Numéro d'application 17142187
Statut En instance
Date de dépôt 2021-01-05
Date de la première publication 2021-07-15
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Zheng, Kang
  • Wang, Yirui
  • Miao, Shun
  • Kuo, Changfu
  • Hsieh, Chen-I

Abrégé

The present disclosure provides a computer-implemented method, a device, and a computer program product for radiographic bone mineral density (BMD) estimation. The method includes receiving a plain radiograph, detecting landmarks for a bone structure included in the plain radiograph, extracting an ROI from the plain radiograph based on the detected landmarks, estimating the BMD for the ROI extracted from the plain radiograph by using a deep neural network.

Classes IPC  ?

  • A61B 6/00 - Appareils pour diagnostic par radiations, p.ex. combinés avec un équipement de thérapie par radiations
  • G06T 7/11 - Découpage basé sur les zones
  • G06T 7/73 - Détermination de la position ou de l'orientation des objets ou des caméras utilisant des procédés basés sur les caractéristiques
  • G06T 7/00 - Analyse d'image
  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
  • G06K 9/46 - Extraction d'éléments ou de caractéristiques de l'image
  • G06N 3/08 - Méthodes d'apprentissage
  • G06N 3/04 - Architecture, p.ex. topologie d'interconnexion
  • G16H 30/40 - TIC spécialement adaptées à la manipulation ou au traitement d’images médicales pour le traitement d’images médicales, p.ex. l’édition
  • G16H 50/30 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicales; TIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour l’évaluation des risques pour la santé d’une personne

40.

METHOD, EQUIPMENT, COMPUTING DEVICE AND COMPUTER-READABLE STORAGE MEDIUM FOR KNOWLEDGE EXTRACTION BASED ON TEXTCNN

      
Numéro d'application 16635554
Statut En instance
Date de dépôt 2019-05-31
Date de la première publication 2021-07-15
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Jin, Ge
  • Xu, Liang
  • Xiao, Jing

Abrégé

The application discloses a method for knowledge extraction based on TextCNN, comprising: S10, collecting first training data, and constructing a character vector dictionary and a word vector dictionary; S20, constructing a first convolutional neural network, and training the first convolutional neural network based on a first optimization algorithm, the first convolutional neural network comprises a first embedding layer, a first multilayer convolution, and a first softmax function connected in turn; S30, constructing a second convolutional neural network, and training the second convolutional neural network based on a second optimization algorithm, the second convolutional neural network comprises a second embedding layer, a second multilayer convolution, a pooling layer, two fully-connected layers and a second softmax function, the second embedding layer connected in turn; S40, extracting a knowledge graph triple of the to-be-predicted data according to an entity tagging prediction output by the first trained convolutional neural network and an entity relationship prediction output by the second trained convolutional neural network.

Classes IPC  ?

  • G06N 5/02 - Représentation de la connaissance
  • G06N 3/08 - Méthodes d'apprentissage
  • G06N 20/10 - Apprentissage automatique utilisant des méthodes à noyaux, p.ex. séparateurs à vaste marge [SVM]
  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques

41.

DEVICE AND METHOD FOR COMPUTER-AIDED DIAGNOSIS BASED ON IMAGE

      
Numéro d'application 16850622
Statut En instance
Date de dépôt 2020-04-16
Date de la première publication 2021-07-15
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Wang, Yirui
  • Chen, Haomin
  • Zheng, Kang
  • Harrison, Adam
  • Lu, Le
  • Miao, Shun

Abrégé

A method for performing computer-aided diagnosis (CAD) based on a medical scan image includes: pre-processing the medical scan image to produce an input image, a flipped image, and a spatial alignment transformation corresponding to the input image and the flipped image; performing Siamese encoding on the input image to produce an encoded input feature map; performing Siamese encoding on the flipped image to produce an encoded flipped feature map; performing a feature alignment using the spatial alignment transformation on the encoded flipped feature map to produce an encoded symmetric feature map; and processing the encoded input feature map and the encoded symmetric feature map to generate a diagnostic result indicating presence and locations of anatomical abnormalities in the medical scan image.

Classes IPC  ?

  • A61B 6/00 - Appareils pour diagnostic par radiations, p.ex. combinés avec un équipement de thérapie par radiations
  • G06K 9/32 - Alignement ou centrage du capteur d'image ou de la zone image
  • G06T 9/00 - Codage d'image
  • G06T 7/00 - Analyse d'image

42.

SENTENCE DISTANCE MAPPING METHOD AND APPARATUS BASED ON MACHINE LEARNING AND COMPUTER DEVICE

      
Numéro d'application 16759368
Statut En instance
Date de dépôt 2019-05-29
Date de la première publication 2021-07-08
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Liu, Yuchao
  • Guo, Dian
  • Han, Ling

Abrégé

A sentence distance mapping method and apparatus based on machine learning, a computer device, and a storage medium are described herein. The method includes: acquiring input single-sentence speech information; converting the single-sentence speech information into single-sentence text information; preprocessing the single-sentence text information, and querying a preset word vector library to obtain a word vector corresponding to each word in the preprocessed single-sentence text information; calculating a distance between the single-sentence text information and a preset standard single sentence by using a preset algorithm based on the word vector corresponding to each word in the single-sentence text information; and inputting the distance into a preset function and obtaining a score through mapping, where the preset function is obtained by performing training on training data.

Classes IPC  ?

43.

METHOD AND DEVICE FOR MARKING TARGET CELLS, STORAGE MEDIUM AND TERMINAL DEVICE

      
Numéro d'application 17207144
Statut En instance
Date de dépôt 2021-03-19
Date de la première publication 2021-07-08
Propriétaire PING AN TECHNOLOGY(SHENZHEN)CO., LTD. (Chine)
Inventeur(s)
  • Guo, Bingxue
  • Wang, Jiaping
  • Xie, Weiwei

Abrégé

A target cell marking method, including: determining an original image format of the original scanned image, and converting the original scanned image into a first image in a preset image format; segmenting the first image into a plurality of image blocks and recording arrangement positions of the image blocks in the first image; respectively inputting the image blocks into a preset deep learning detection model to obtain first position information of target cells in the image blocks; determining second position information of the target cells in the first image according to the first position information and the corresponding arrangement positions; integrating the image blocks according to the arrangement positions to obtain a second image, and marking the target cells in the second image; and converting the second image marked by the target cells into a third image in the original image format, and displaying the third image.

Classes IPC  ?

  • G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
  • G06T 7/73 - Détermination de la position ou de l'orientation des objets ou des caméras utilisant des procédés basés sur les caractéristiques
  • G06T 7/11 - Découpage basé sur les zones
  • G06K 9/03 - Détection ou correction d'erreurs, p.ex. par une seconde exploration
  • G06T 11/00 - Génération d'images bidimensionnelles [2D]

44.

Cultivated land recognition method in satellite image and computing device

      
Numéro d'application 16727753
Numéro de brevet 11157737
Statut Délivré - en vigueur
Date de dépôt 2019-12-26
Date de la première publication 2021-07-01
Date d'octroi 2021-10-26
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Zhao, Yi
  • Qiao, Nan
  • Lin, Ruei-Sung
  • Gong, Bo
  • Han, Mei

Abrégé

A cultivated land recognition method in a satellite image includes: segmenting a satellite image of the Earth into a plurality of standard images; and recognizing cultivated land area in each of the standard images using a cultivated land recognition model to obtain a plurality of first images. Edges of ground level entities in each of the standard images are detected using an edge detection model to obtain a plurality of second images. Each of the first images and a corresponding one of the second images is merged to obtain a plurality of third images; and cultivated land images is obtained by segmenting each of the third images using a watershed segmentation algorithm. Not only can a result of recognizing cultivated land in satellite images of the Earth be improved, but an efficiency of recognizing the cultivated land also be improved. A computing device employing the method is also disclosed.

Classes IPC  ?

  • G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
  • G06T 7/13 - Détection de bords
  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
  • G06F 17/18 - Opérations mathématiques complexes pour l'évaluation de données statistiques

45.

Face swap method and computing device

      
Numéro d'application 16729165
Numéro de brevet 11120595
Statut Délivré - en vigueur
Date de dépôt 2019-12-27
Date de la première publication 2021-07-01
Date d'octroi 2021-09-14
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Miao, Jinghong
  • Gou, Yuchuan
  • Li, Minghao
  • Lai, Jui-Hsin
  • Gong, Bo
  • Han, Mei

Abrégé

In a face swap method carried out by an electronic device, a first head image is segmented from a destination image. First facial landmarks and a first hair mask are obtained according to the first head image. A second head image is segmented from a source image. Second facial landmarks and a second hair mask are obtained according to the second head image. If at least one eye landmark in the second facial landmarks is covered by hair, the second head image and the second hair mask are processed and repaired so as to obtain a swapped-face image with eyes not covered by hair.

Classes IPC  ?

  • G06T 11/60 - Edition de figures et de texte; Combinaison de figures ou de texte
  • G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
  • G06K 9/34 - Découpage des formes se touchant ou se chevauchant dans la zone image

46.

INTELLIGENT MOBILITY ASSISTANCE DEVICE

      
Numéro d'application 16729184
Statut En instance
Date de dépôt 2019-12-27
Date de la première publication 2021-07-01
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Qin, Chaoping
  • Xia, Tian
  • Han, Mei
  • Chang, Peng
  • Gong, Bo

Abrégé

A device providing intelligent assistance in mobility for disabled people and others includes a mobility device and a lifting device detachably mounted on the mobility device. The lifting device includes a base frame, a retractable bracket structure, several wheels, a sitting pad, and a backrest. The wheels are mounted on a lower surface of the base frame and drive the lifting device to move. The retractable bracket structure is mounted on an upper surface of the base frame. The sitting pad is detachably mounted on the retractable bracket structure, and the backrest is rotatably mounted on the retractable bracket structure.

Classes IPC  ?

  • A61G 7/10 - Dispositifs pour soulever les malades ou les personnes handicapées, p.ex. adaptations particulières d'appareils de levage à cet effet

47.

Environment monitoring method and electronic device

      
Numéro d'application 16727763
Numéro de brevet 11176371
Statut Délivré - en vigueur
Date de dépôt 2019-12-26
Date de la première publication 2021-07-01
Date d'octroi 2021-11-16
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Yao, Xi
  • Chen, Qi
  • Lin, Ruei-Sung
  • Gong, Bo
  • Zhao, Yi
  • Han, Mei
  • Miao, Jinghong

Abrégé

An environment monitoring method and an electronic device are provided, the method divides the satellite image into a plurality of first divided images with overlapping areas, a first multi-dimensional feature map is obtained by inputting the plurality of first divided images into an environment monitoring model, the environmental monitoring model fully combines the correlation between the environmental information of different dimensions, the environmental features of a plurality of different dimensions are correlated through an association network. By utilizing the environment monitoring method, a large area of the environment monitoring effectively is realized, and accuracy of environmental detection is improved.

Classes IPC  ?

  • G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
  • G06K 9/46 - Extraction d'éléments ou de caractéristiques de l'image
  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques

48.

CROP IDENTIFICATION METHOD AND COMPUTING DEVICE

      
Numéro d'application 16727788
Statut En instance
Date de dépôt 2019-12-26
Date de la première publication 2021-07-01
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Lin, Ruei-Sung
  • Qiao, Nan
  • Zhao, Yi
  • Gong, Bo
  • Han, Mei

Abrégé

In a crop identification method, multi-temporal sample remote sensing images labeled with first planting blocks of a specific crop are acquired. NDVI data of the sample remote sensing images are calculated. Noise of the NDVI data is reduced. A first multivariate Gaussian model is fitted based on de-noised NDVI data of the sample remote sensing image. Multi-temporal target remote sensing images are acquired. An NDVI time series of each pixel in the target remote sensing image is constructed. The NDVI time series is input to the first multivariate Gaussian model to obtain a likelihood value of each pixel displaying the specific crop in the remote sensing images. Second planting blocks of the specific crop in the target remote sensing images are determined accordingly. An accurate and robust identification result is thereby achieved.

Classes IPC  ?

  • G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
  • G06T 5/00 - Amélioration ou restauration d'image
  • G06T 5/20 - Amélioration ou restauration d'image en utilisant des opérateurs locaux
  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques

49.

Image processing method and electronic device

      
Numéro d'application 16727791
Numéro de brevet 11080834
Statut Délivré - en vigueur
Date de dépôt 2019-12-26
Date de la première publication 2021-07-01
Date d'octroi 2021-08-03
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Miao, Jinghong
  • Gou, Yuchuan
  • Gong, Bo
  • Han, Mei

Abrégé

An image processing method and an electronic device are provided, the method extracts a first object mask of a texture image and a second object mask of a to-be-optimized image. An image recognition model is used to obtain a first content matrix, a first texture matrix, a second content matrix, a second texture matrix, a first mask matrix, and a second mask matrix. A total loss of the to-be-optimized image is determined, and the total loss is minimized by adjusting a value of each pixel of the to-be-optimized image, thereby an optimized image is obtained. By utilizing the image processing method, quality of final image is improved.

Classes IPC  ?

  • G06T 5/50 - Amélioration ou restauration d'image en utilisant plusieurs images, p.ex. moyenne, soustraction
  • G06F 17/16 - Calcul de matrice ou de vecteur
  • G06N 3/04 - Architecture, p.ex. topologie d'interconnexion

50.

Method for generating model of sculpture of face, computing device, and non-transitory storage medium

      
Numéro d'application 16729117
Numéro de brevet 11062504
Statut Délivré - en vigueur
Date de dépôt 2019-12-27
Date de la première publication 2021-07-01
Date d'octroi 2021-07-13
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Li, Minghao
  • Miao, Jinghong
  • Gou, Yuchuan
  • Gong, Bo
  • Han, Mei

Abrégé

A method for generating a model for facial sculpture based on a generative adversarial network (GAN) includes training a predetermined GAN based on a three dimensional (3D) face dataset of multiple 3D face images to obtain an initial sculpture generation model. A curvature conversion on each of the multiple 3D face images is performed to obtain a distribution map of curvature value and the distribution map of curvature value of each of the multiple 3D face images is added as attention information to the initial sculpture generation model, to train and generate a face sculpture generation model. A target 3D face data and predetermined face curvature parameters are received, and the target 3D face data and the predetermined face curvature parameters are inputted into the face sculpture generation model to generate a face sculpture model. A computing device using the method is also provided.

Classes IPC  ?

  • G06T 15/20 - Calcul de perspectives
  • G06T 5/00 - Amélioration ou restauration d'image
  • G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales

51.

DRIVING MODEL TRAINING METHOD, DRIVER IDENTIFICATION METHOD, APPARATUSES, DEVICE AND MEDIUM

      
Numéro d'application 16093633
Statut En instance
Date de dépôt 2017-10-31
Date de la première publication 2021-06-24
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Jin, Xin
  • Wu, Zhuangwei
  • Zhang, Chuan
  • Zhao, Yuanyuan
  • Huang, Duxin
  • Liang, Yongjian
  • Huo, Li

Abrégé

A driving model training method, a driver identification method, apparatuses, a device and a medium are provided. The driving model training method comprises: acquiring training behavior data of a user wherein the training behavior data are associated with a user identifier; acquiring training driving data associated with the user identifier based on the training behavior data; acquiring positive and negative samples from the training driving data based on the user identifier, and dividing the positive and negative samples into a training set and a test set; training the training set using a bagging algorithm, and acquiring an original driving model; and testing the original driving model using the test set, and acquiring a target driving model. The driving model training method effectively enhances generalization of the driving model, solves the problem of a poor identification result of the current driving identification model.

Classes IPC  ?

  • B60W 40/09 - Style ou comportement de conduite
  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
  • G06N 3/08 - Méthodes d'apprentissage

52.

Vehicle damage detection method based on image analysis, electronic device and storage medium

      
Numéro d'application 16726790
Numéro de brevet 11120308
Statut Délivré - en vigueur
Date de dépôt 2019-12-24
Date de la première publication 2021-06-24
Date d'octroi 2021-09-14
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Li, Kun
  • Zhang, Hao
  • Lin, Ruei-Sung
  • Han, Mei

Abrégé

A vehicle damage detection method based on image analysis, an electronic device, and a storage medium are provided. In the vehicle damage detection method, query images are obtained by filtering received images through a pre-trained Single Shot MultiBox Detector (SSD) object detection model, and a feature vector of each of the query images is obtained by inputting each of the query images into a residual network. Target output data is obtained using a Transformer model, similar images of the query images are obtained by processing the target output data using a pre-trained similarity judgment model. Loss of a current vehicle damage assessment case is evaluated based on similar cases, and evaluated loss is outputted. By utilizing the vehicle damage detection method, effectiveness of the vehicle damage detection is improved, and automatic evaluation of a loss is achieved.

Classes IPC  ?

  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques

53.

Method for training image generation model and computer device

      
Numéro d'application 16726785
Numéro de brevet 11048971
Statut Délivré - en vigueur
Date de dépôt 2019-12-24
Date de la première publication 2021-06-24
Date d'octroi 2021-06-29
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Miao, Jinghong
  • Gong, Bo
  • Han, Mei

Abrégé

In a method for training an image generation model, a first generator generates a first sample matrix, a first converter generates a sample contour image, a first discriminator optimizes the first generator and the first converter, a second generator generates a second sample matrix according to the first sample matrix, a second converter generates a first sample grayscale image, a second discriminator optimizes the second generator and the second converter, a third generator generates a third sample matrix according to the second sample matrix, a third converter generates a second sample grayscale image, a third discriminator optimizes the third generator and the third converter, a fourth generator generates a fourth sample matrix according to the third sample matrix, a fourth converter generates a sample color image, and a fourth discriminator optimizes the fourth generator and the fourth converter. The image generation model can be trained easily.

Classes IPC  ?

  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques

54.

METHOD, APPARATUS AND DEVICE FOR VOICEPRINT RECOGNITION, AND MEDIUM

      
Numéro d'application 16091926
Statut En instance
Date de dépôt 2018-02-09
Date de la première publication 2021-06-24
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Wang, Jianzong
  • Luo, Jian
  • Guo, Hui
  • Xiao, Jing

Abrégé

The present solution provides a method, apparatus and device for voiceprint recognition and a medium, which is applicable to the technical field of Internet. The method includes: establishing and training a universal recognition model, wherein the universal recognition model is indicative of a distribution of voice features under a preset communication medium; acquiring voice data under the preset communication medium; creating a corresponding voiceprint vector according to the voice data; and determining a voiceprint feature corresponding to the voiceprint vector according to the universal recognition model. According to the present solution, the voice data is processed by establishing and training the universal recognition model, so that a corresponding voiceprint vector is obtained, a voiceprint feature is determined and a person who makes a sound is recognized according to the voiceprint feature. Since the universal recognition model does not limit contents of the voice, the voiceprint recognition can be used more flexibly and usage scenarios of the voiceprint recognition are increased.

Classes IPC  ?

  • G10L 17/04 - Entraînement, enrôlement ou construction de modèle
  • G10L 17/02 - Opérations de prétraitement, p.ex. sélection de segment; Représentation ou modélisation de motifs, p.ex. fondée sur l’analyse linéaire discriminante [LDA] ou les composantes principales; Sélection ou extraction des caractéristiques
  • G10L 17/06 - Techniques de prise de décision; Stratégies d’alignement de motifs
  • G10L 25/18 - Techniques d'analyses de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par le type de paramètres extraits les paramètres extraits étant l’information spectrale de chaque sous-bande

55.

FINANCIAL TRANSACTION MANAGEMENT SYSTEM, METHOD, STORAGE MEDIUM AND SERVER

      
Numéro d'application 16077033
Statut En instance
Date de dépôt 2017-06-26
Date de la première publication 2021-06-17
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Liu, Xing
  • Jiang, Bo
  • Hu, Kaihao
  • Qiu, Yi

Abrégé

A financial transaction management, method, storage medium and server, the server comprise a client terminal and a server, the client terminal is configured to receive an account login request inputted by a user, and transmit the account login request to the server; the server is configured to receive the account login request, and judge whether there exists a dedicated account corresponding to the dedicated account ID, and transmit a first control signal to the client terminal when there exists the dedicated account; the client terminal is further configured to receive the first control signal and enter a dedicated account interface according to the first control signal, receive a first transaction request inputted by the user and transmit the first transaction request to the server; the first transaction request includes the dedicated account information and transaction information associated with the dedicated account ID; the server is further configured to receive the first transaction request, and accomplish a transaction based on the first transaction request. There is no need for the financial transaction management system to login the dedicated account interface through the dedicated account and perform a transaction, an operation process of the financial transaction management system is easy and convenient.

Classes IPC  ?

  • G06Q 40/02 - Opérations bancaires, p.ex. calcul d'intérêts, autorisations de crédit, hypothèques, banque à domicile ou banque en ligne
  • G06Q 30/00 - Commerce, p.ex. achat ou vente, ou commerce électronique

56.

SIP INFORMATION ANALYSIS METHOD AND DEVICE, SERVER, AND MEDIUM

      
Numéro d'application 16090589
Statut En instance
Date de dépôt 2018-01-31
Date de la première publication 2021-06-17
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Zhang, Xiukai
  • Fan, Enyan
  • Qiao, Lei
  • Liu, Guangwei

Abrégé

The present application is applicable to the technical field of communication, and provides a session initiation protocol (SIP) information analysis method and device, a server, and a medium. The method includes adding a header field identifier to each of SIP messages; performing packet capture on each of the SIP messages to respectively obtain a first SIP message and a second SIP message when each of the SIP messages passes through an external network switch and an internal network switch; performing matching identification on each of the first SIP messages and each of the second SIP messages according to the header field identifier of each of the SIP messages, to determine a first SIP message and a second SIP message having the same header field identifier; and analyzing the SIP messages according to the first SIP message and the second SIP message having the same header field identifier. Through the above SIP information analysis method and the server, SIP messages having problems in the cross-domain process can be detected, and the SIP messages with the problems can also be analyzed.

Classes IPC  ?

  • H04L 29/08 - Procédure de commande de la transmission, p.ex. procédure de commande du niveau de la liaison
  • H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole

57.

METHOD FOR ACCELERATED DETECTION OF OBJECT IN VIDEOS, SERVER, AND NON-TRANSITORY COMPUTER READABLE STORAGE MEDIUM

      
Numéro d'application 17167515
Statut En instance
Date de dépôt 2021-02-04
Date de la première publication 2021-06-17
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s) Ye, Ming

Abrégé

A method for accelerated detection of objects in videos, a server, and a non-transitory computer readable storage medium are provided. The method realizes the detection of a target object in a video by dividing all frame images in video images into preset groups of frame images, each group of frame images including a keyframe image and a non-keyframe image, using a detection box of a target in the keyframe image to generate a preselection box in the non-keyframe image, and detecting the location of the target in the preselection box.

Classes IPC  ?

  • G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
  • G06K 9/46 - Extraction d'éléments ou de caractéristiques de l'image
  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
  • G06T 3/40 - Changement d'échelle d'une image entière ou d'une partie d'image
  • G06N 3/08 - Méthodes d'apprentissage

58.

TEXT-BASED SPEECH SYNTHESIS METHOD, COMPUTER DEVICE, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM

      
Numéro d'application 17178823
Statut En instance
Date de dépôt 2021-02-18
Date de la première publication 2021-06-10
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Chen, Minchuan
  • Ma, Jun
  • Wang, Shaojun

Abrégé

A text-based speech synthesis method, a computer device, and a non-transitory computer-readable storage medium are provided. The text-based speech synthesis method includes: a target text to be recognized is obtained; each character in the target text is discretely characterized to generate a feature vector corresponding to each character; the feature vector is input into a pre-trained spectrum conversion model, to obtain a Mel-spectrum corresponding to each character in the target text output by the spectrum conversion model; and the Mel-spectrum is converted to speech to obtain speech corresponding to the target text.

Classes IPC  ?

  • G10L 13/08 - Analyse de texte ou génération de paramètres pour la synthèse de la parole à partir de texte, p.ex. conversion graphème-phonème, génération de prosodie ou détermination de l'intonation ou de l'accent tonique
  • G10L 25/24 - Techniques d'analyses de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par le type de paramètres extraits les paramètres extraits étant le cepstre
  • G10L 25/18 - Techniques d'analyses de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par le type de paramètres extraits les paramètres extraits étant l’information spectrale de chaque sous-bande
  • G10L 13/047 - Architecture des synthétiseurs de parole

59.

FINGER VEIN COMPARISON METHOD, COMPUTER EQUIPMENT, AND STORAGE MEDIUM

      
Numéro d'application 17178911
Statut En instance
Date de dépôt 2021-02-18
Date de la première publication 2021-06-10
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Chao, Zhongdi
  • Zhuang, Bojin
  • Wang, Shaojun

Abrégé

A finger vein comparison method, a computer equipment, and a storage medium are provided. The finger vein comparison method includes: two finger vein images to be compared are obtained (S10); image channel fusion is performed on the two finger vein images to be compared to obtain a two-channel target finger vein image to be compared (S20); the target finger vein image to be compared is input into a feature extractor, and a feature vector of the target finger vein image to be compared is extracted by the feature extractor (S30); the feature vector of the target finger vein image to be compared is input into a dichotomy classifier to obtain a dichotomy result (S40); and it is determined according to the dichotomy result whether the two finger vein images to be compared come from the same finger (S50).

Classes IPC  ?

  • G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques

60.

Scoring information matching method and device, storage medium and server

      
Numéro d'application 16076583
Numéro de brevet 11113706
Statut Délivré - en vigueur
Date de dépôt 2017-06-26
Date de la première publication 2021-06-10
Date d'octroi 2021-09-07
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Chen, Bin
  • Zhang, Xinyu
  • Wang, Wei
  • Li, Pingmei

Abrégé

Scoring information matching method and device, storage device and server. This scoring information matching method comprises: obtaining a target scoring information and a target scoring message which corresponds to the target scoring information; obtaining a first telephone number which sends out the target scoring message; obtaining the second telephone number which sends out the target scoring information; extracting a first identity number from the first telephone number; searching in preset service records for a service record of which an identity number is the same as the first identity number, a telephone number of a recipient of a corresponding scoring message is the same as the second telephone number, and a transmission time of the corresponding scoring message satisfies a preset condition; and determining the searched service record as a target service record that matches with the target scoring information.

Classes IPC  ?

  • G06Q 30/02 - Marketing, p.ex. études et analyse de marchés, prospection, promotions, publicité, établissement du profil des acheteurs, gestion ou fidélisation de clientèle; Estimation ou détermination des prix
  • G06Q 30/00 - Commerce, p.ex. achat ou vente, ou commerce électronique
  • H04M 3/51 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur
  • H04M 3/42 - Systèmes fournissant des fonctions ou des services particuliers aux abonnés

61.

METHOD AND DEVICE FOR DETECTING AND LOCATING LESION IN MEDICAL IMAGE, EQUIPMENT AND STORAGE MEDIUM

      
Numéro d'application 17168884
Statut En instance
Date de dépôt 2021-02-05
Date de la première publication 2021-06-03
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Wang, Yue
  • Lv, Bin
  • Lv, Chuanfeng

Abrégé

A method for detecting and locating a lesion in a medical image is provided. A target medical image of a lesion is obtained and input into a deep learning model to obtain a target sequence. A first feature map output from the last convolution layer in the deep learning model is extracted. A weight value of each network unit corresponding to each preset lesion type in a fully connected layer is extracted. For each preset lesion type, a fusion feature map is calculated according to the first feature map and the corresponding weight value and resampled to the size of the target medical image to generate a generic activation map. The maximum connected area in each generic activation map is determined, and a mark border surrounding the maximum connected area is created. A mark border corresponding to each preset lesion type is added to the target medical image.

Classes IPC  ?

  • G06T 7/00 - Analyse d'image
  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
  • G06K 9/46 - Extraction d'éléments ou de caractéristiques de l'image
  • G06T 7/73 - Détermination de la position ou de l'orientation des objets ou des caméras utilisant des procédés basés sur les caractéristiques
  • G06T 7/11 - Découpage basé sur les zones
  • G06T 7/136 - Découpage; Détection de bords impliquant un seuillage
  • G06T 7/187 - Découpage; Détection de bords impliquant un étiquetage de composantes connexes
  • A61B 5/00 - Mesure servant à établir un diagnostic ; Identification des individus
  • A61B 6/03 - Tomographes assistés par ordinateur

62.

METHOD AND TERMINAL FOR GENERATING A TEXT BASED ON SELF-ENCODING NEURAL NETWORK, AND MEDIUM

      
Numéro d'application 16637274
Statut En instance
Date de dépôt 2019-06-26
Date de la première publication 2021-06-03
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Jin, Ge
  • Xu, Liang
  • Xiao, Jing

Abrégé

The present disclosure relates to the technical field of natural language understanding, and provides a method, a terminal and a medium for generating a text based on a self-encoding neural network. The method includes: obtaining a text word vector and a classification requirement of a statement to be input; reversely inputting the text word vector into a trained self-encoding neural network model to obtain a hidden feature of an intermediate hidden layer of the self-encoding neural network model; modifying the hidden feature according to a preset classification scale and the classification requirement; defining the modified hidden feature as the intermediate hidden layer of the self-encoding neural network model, and reversely generating a word vector corresponding to an input layer of the self-encoding neural network model by the intermediate hidden layer; and generating the corresponding text, according to the generated word vector.

Classes IPC  ?

  • G06F 40/40 - Traitement ou traduction du langage naturel
  • G06N 3/04 - Architecture, p.ex. topologie d'interconnexion
  • G06N 3/08 - Méthodes d'apprentissage

63.

IMAGE GENERATION METHOD AND COMPUTING DEVICE

      
Numéro d'application 16701484
Statut En instance
Date de dépôt 2019-12-03
Date de la première publication 2021-06-03
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Miao, Jinghong
  • Gou, Yuchuan
  • Lin, Ruei-Sung
  • Gong, Bo
  • Han, Mei

Abrégé

An image generation method and a computing device using the method, includes creating an image database with a plurality of original images, and obtaining a plurality of first outline images of an object by detecting an outline of the object in each of the original images. Numerous first feature matrixes are obtained by calculating a feature matrix of each of the first outline images. A second feature matrix of a second outline image input by a user is calculated. A target feature matrix is selected from the plurality of first feature matrixes, the target feature matrix has a minimum difference as the second feature matrix. A target image corresponding to the target feature matrix is matched and displayed from the image database. The method and device allow detection of an object outline in an image input by users and the generation of an image with the detected outline.

Classes IPC  ?

  • G06K 9/48 - Extraction d'éléments ou de caractéristiques de l'image en codant le contour de la forme
  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
  • G06K 9/46 - Extraction d'éléments ou de caractéristiques de l'image
  • G06T 7/13 - Détection de bords
  • G06T 3/40 - Changement d'échelle d'une image entière ou d'une partie d'image
  • G06K 9/42 - Normalisation des dimensions de la forme
  • G06F 16/538 - Présentation des résultats des requêtes
  • G06F 16/56 - Recherche d’informations; Structures de bases de données à cet effet; Structures de systèmes de fichiers à cet effet de données d’images fixes en format vectoriel
  • G06N 3/04 - Architecture, p.ex. topologie d'interconnexion
  • G06N 3/08 - Méthodes d'apprentissage

64.

IMAGE GENERATION METHOD AND COMPUTING DEVICE

      
Numéro d'application 16701474
Statut En instance
Date de dépôt 2019-12-03
Date de la première publication 2021-06-03
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Gou, Yuchuan
  • Miao, Jinghong
  • Lin, Ruei-Sung
  • Gong, Bo
  • Han, Mei

Abrégé

An image generation method and a computing device employing the method includes: acquiring a plurality of original images; and processing the plurality of original images to obtain a training data set. An anti-neural network model is trained according to the training data set. A candidate image is generated through the trained anti-neural network model. The candidate image is complemented through a detail completion network model to obtain a target image according to a comparison image. Thereby, a style of the generated image is the same as that of the comparison image. A more realistic image can be randomly generated saving the time and energy of artificially creating an image.

Classes IPC  ?

  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
  • G06T 3/40 - Changement d'échelle d'une image entière ou d'une partie d'image
  • G06N 3/08 - Méthodes d'apprentissage
  • G06N 3/04 - Architecture, p.ex. topologie d'interconnexion

65.

UNBALANCED SAMPLE DATA PREPROCESSING METHOD AND DEVICE, AND COMPUTER DEVICE

      
Numéro d'application 17165640
Statut En instance
Date de dépôt 2021-02-02
Date de la première publication 2021-05-27
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Yu, Xiuming
  • Wang, Wei
  • Xiao, Jing

Abrégé

Provided is an unbalanced sample data preprocessing method, which includes: a data acquisition request is received and initial data is acquired according to the data acquisition request, and the initial data is classified according to a preset classification rule to obtain first-class sample sets and second-class sample sets; characteristics of K first sample points extracted are analyzed to obtain a new data characteristic of the first-class sample sets; a new data label of the first-class sample sets is generated according to a first label corresponding to the first-class sample sets; a ratio between the number of first-class sample sets and the number of second-class sample sets is calculated; and new data of the first-class sample sets is generated according to the new data characteristic and the new data label, and the amount of new data is adjusted according to the ratio to increase the number of first-class sample sets.

Classes IPC  ?

  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
  • G06F 7/24 - Tri, c. à d. extraction de données d'un ou de plusieurs supports, nouveau rangement des données dans un ordre de succession numérique ou autre, et réinscription des données triées sur le support original ou sur un support différent ou sur une série d

66.

MAN-MACHINE INTERACTION METHOD AND SYSTEM, COMPUTER DEVICE, AND STORAGE MEDIUM

      
Numéro d'application 17167466
Statut En instance
Date de dépôt 2021-02-04
Date de la première publication 2021-05-27
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s) Chen, Lin

Abrégé

The application discloses a main-machine interaction method and system, a computer device, and a storage medium. The method includes: an interaction end collects user information including biological sample information and preprocesses and filters the user information, and sends the preprocessed information to a central server; the central server assigns a biological recognition task and distributes the biological recognition task to a computing server; the computing server extracts biological characteristics from the biological sample information according to the biological recognition task, and returns obtained extraction results to the central server; the central server combines the extraction results to get a processing result; the processing result is returned to the interaction end; the interaction end responds to the processing result to complete a man-machine interaction with the user.

Classes IPC  ?

  • G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
  • G10L 17/22 - Procédures interactives; Interfaces homme-machine

67.

INTELLIGENT DATA ANALYSIS METHOD AND DEVICE, COMPUTER DEVICE, AND STORAGE MEDIUM

      
Numéro d'application 17168925
Statut En instance
Date de dépôt 2021-02-05
Date de la première publication 2021-05-27
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Chen, Xianxian
  • Ruan, Xiaowen
  • Xu, Liang

Abrégé

The application discloses an intelligent data analysis method and device, a computer device, and a storage medium. The intelligent data analysis method includes that: a public opinion factor obtained and a public opinion index carrying a time label are taken as first portrait data (S40); original sample data is obtained based on the first portrait data and medical data; the original sample data is cleaned to obtain sample data to be processed (S50); lag processing is performed on the sample data to be processed to obtain lag sample data (S60); feature expansion is performed on the lag sample data to obtain target sample data (S70); and an improved multi-granularity cascading random forest algorithm is used to train the target sample data to obtain a target forecast model (S80); the improved multi-granularity cascading random forest algorithm includes a pooling layer, which is used for retaining data features (S90).

Classes IPC  ?

  • G16H 50/70 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicales; TIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour extraire des données médicales, p.ex. pour analyser les cas antérieurs d’autres patients
  • G06N 20/20 - Techniques d’ensemble en apprentissage automatique

68.

ADVERTISEMENT GENERATION METHOD, COMPUTER READABLE STORAGE MEDIUM AND SYSTEM

      
Numéro d'application 16085017
Statut En instance
Date de dépôt 2017-09-30
Date de la première publication 2021-04-29
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Shi, Guanghui
  • Wang, Jianming
  • Xiao, Jing

Abrégé

The disclosure relates to an advertisement generation method and system. The advertisement generation method includes: acquiring click data of the advertisements subjected to advertisement exposure triggered by each user from various predetermined data source servers, and extracting picture style features of advertisement background pictures in the advertisement click data; during recommending of advertisements to predetermined users, analyzing the advertisement click data of the various users according to predetermined picture style features and a predetermined first analysis rule to obtain picture style features of advertisement pictures to be recommended corresponding to the various users; and generating recommended advertisements according to the obtained picture style features corresponding to the various users to recommend the recommended advertisements to the corresponding users. The disclosure can objectively or adaptively integrate the picture style features of other advertisements to improve the acceptance of advertisement and improve the advertisement production efficiency.

Classes IPC  ?

  • G06Q 30/02 - Marketing, p.ex. études et analyse de marchés, prospection, promotions, publicité, établissement du profil des acheteurs, gestion ou fidélisation de clientèle; Estimation ou détermination des prix
  • G06N 5/04 - Méthodes ou dispositifs inférents

69.

NETWORK ACTIVITY INDICATOR PRESENTATION METHOD, ELECTRONIC DEVICE, COMPUTER-READABLE STORAGE MEDIUM AND SYSTEM

      
Numéro d'application 16085026
Statut En instance
Date de dépôt 2017-09-30
Date de la première publication 2021-04-29
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s) He, Bing

Abrégé

The disclosure relates to a network activity indicator presentation method and system. The method includes: monitoring a setting state of a visible attribute of a network activity indicator, wherein the setting state of the visible attribute includes: setting to be a YES state and setting to be a NO state; calculating a count value of the network activity indicator according to the monitored setting state of the visible attribute; and acquiring the count value corresponding to the network activity indicator, and determining a presentation state of the network activity indicator, wherein the presentation state of the network activity indicator includes: a display state and a non-display state. The disclosure has the beneficial effects of simplifying programmed algorithms and saving system resources, the implementation process is brief, execution efficiency is high, and an occupation rate of the system resources is greatly reduced.

Classes IPC  ?

  • H04L 12/26 - Dispositions de surveillance; Dispositions de test
  • G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p.ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comport
  • G06F 11/30 - Surveillance du fonctionnement

70.

METHOD, DEVICE, STORAGE MEDIUM AND TERMINAL FOR MODIFYING ACCOUNT NAME

      
Numéro d'application 16092760
Statut En instance
Date de dépôt 2018-02-27
Date de la première publication 2021-04-29
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Li, Shengsheng
  • Zhu, Xiaoyu

Abrégé

Provided are a method, a device, a storage medium, and a terminal for modifying account name, comprising: generating an account name modification request and calling a first modification interface to send the modification request to a server upon the condition that the case status information is that the self-service claim settlement is under review; receiving the modification request through the first modification interface and modifying the account name of the self-service claim settlement according to the request; calling a second modification interface to send the modification request to the server upon the condition that the case status information is that the self-service claim settlement is in a settled state and the transfer for the self-service claim settlement fails due to incorrect account information; receiving the modification request through the second modification interface and modifying the account name of the self-service claim settlement, re-initiating the transfer for the self-service claim settlement.

Classes IPC  ?

  • G06Q 40/08 - Assurance, p.ex. analyse des risques ou pensions

71.

Method and device for customer resource acquisition, terminal device and storage medium

      
Numéro d'application 16095803
Numéro de brevet 11122128
Statut Délivré - en vigueur
Date de dépôt 2018-01-23
Date de la première publication 2021-04-29
Date d'octroi 2021-09-14
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s) Yan, Baohang

Abrégé

The present application discloses a method and a device for customer resource acquisition, a terminal device and a storage medium. The method for customer resource acquisition includes: acquiring user's access request which includes a session identifier, user information and a progress identifier; determining whether the progress identifier is a completed identifier; determining whether the user's access request is a first access request corresponding to the session identifier; if the progress identifier is a completed identifier and the user's access request is not a first access request, determining a corresponding administration process based on the session identifier; storing the user information in an address space corresponding to the administration process, generating a first resource data based on all user information in the address space, uploading the first resource data to server, and destroying the administration process. The method for customer resource acquisition is highly efficient with good database performance.

Classes IPC  ?

  • G06F 15/16 - Associations de plusieurs calculateurs numériques comportant chacun au moins une unité arithmétique, une unité programme et un registre, p.ex. pour le traitement simultané de plusieurs programmes
  • H04L 29/08 - Procédure de commande de la transmission, p.ex. procédure de commande du niveau de la liaison
  • G06F 40/174 - Remplissage de formulaires; Fusion

72.

Acoustic model training method, speech recognition method, apparatus, device and medium

      
Numéro d'application 16097850
Numéro de brevet 11030998
Statut Délivré - en vigueur
Date de dépôt 2017-08-31
Date de la première publication 2021-04-29
Date d'octroi 2021-06-08
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Liang, Hao
  • Wang, Jianzong
  • Cheng, Ning
  • Xiao, Jing

Abrégé

An acoustic model training method, a speech recognition method, an apparatus, a device and a medium. The acoustic model training method comprises: performing feature extraction on a training speech signal to obtain an audio feature sequence; training the audio feature sequence by a phoneme mixed Gaussian Model-Hidden Markov Model to obtain a phoneme feature sequence; and training the phoneme feature sequence by a Deep Neural Net-Hidden Markov Model-sequence training model to obtain a target acoustic model. The acoustic model training method can effectively save time required for an acoustic model training, improve the training efficiency, and ensure the recognition efficiency.

Classes IPC  ?

  • G10L 15/14 - Classement ou recherche de la parole utilisant des modèles statistiques, p.ex. des modèles de Markov cachés [HMM]
  • G10L 15/02 - Extraction de caractéristiques pour la reconnaissance de la parole; Sélection d'unités de reconnaissance 
  • G10L 15/16 - Classement ou recherche de la parole utilisant des réseaux neuronaux artificiels

73.

Multi-task scheduling method and system, application server and computer-readable storage medium

      
Numéro d'application 16084980
Numéro de brevet 11061925
Statut Délivré - en vigueur
Date de dépôt 2017-08-31
Date de la première publication 2021-04-29
Date d'octroi 2021-07-13
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s) Fu, Jun

Abrégé

A multi-task scheduling method and system, an application server and a computer-readable storage medium are provided. The method includes: establishing a first connection between a data platform and at least one data source, and establishing a second connection between the data platform and the application server; receiving source tables selected by a user to be synchronized and data source types, generating a table creation task and data synchronization task corresponding to each data source, and distributing them to a preset workflow scheduling engine; when synchronization starting time selected by the user is reached, calling a preset task scheduling interface template through the preset workflow scheduling engine, and transmitting synchronization parameters to the task scheduling interface template; and calling a corresponding task execution script in the task scheduling interface template according to the synchronization parameters, and executing the table creation task and data synchronization task corresponding to each data source.

Classes IPC  ?

  • G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuées; Architectures de systèmes de bases de données distribuées à cet effet
  • G06F 16/21 - Conception, administration ou maintenance des bases de données
  • G06F 9/48 - Lancement de programmes; Commutation de programmes, p.ex. par interruption

74.

Method and device for acquiring slant value of slant image, terminal and storage medium

      
Numéro d'application 16090198
Numéro de brevet 11074443
Statut Délivré - en vigueur
Date de dépôt 2017-08-30
Date de la première publication 2021-04-29
Date d'octroi 2021-07-27
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Wang, Jianzong
  • Wang, Chenyu
  • Ma, Jin
  • Xiao, Jing

Abrégé

A method, a device, a terminal and a storage medium for acquiring slant value of slant image are provided. The method for acquiring slant value of a slant image comprises: analyzing the slant image and acquiring coordinate information of a plurality of boundary lines of the slant image; acquiring first slant values of the boundary lines by analysing and calculating the coordinate information; acquiring a correction value; calculating difference values between the first slant values and the correction value respectively; determining the first slant value corresponding to the minimum difference value as the slant value of the slant image. The technical solution of the present disclosure can uniquely determine a slant value of slant image.

Classes IPC  ?

  • G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
  • G06T 7/12 - Découpage basé sur les bords
  • G06K 9/38 - Quantification du signal image analogique
  • G06K 9/46 - Extraction d'éléments ou de caractéristiques de l'image
  • G06T 7/60 - Analyse des attributs géométriques
  • G06T 7/11 - Découpage basé sur les zones
  • G06K 9/32 - Alignement ou centrage du capteur d'image ou de la zone image

75.

ELECTRONIC DEVICE, METHOD FOR CONSTRUCTING SCORING MODEL OF RETAIL OUTLETS, SYSTEM, AND COMPUTER READABLE MEDIUM

      
Numéro d'application 16097273
Statut En instance
Date de dépôt 2017-10-31
Date de la première publication 2021-04-29
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Deng, Kun
  • Han, Wei
  • Wang, Jianming
  • Xiao, Jing

Abrégé

The present disclosure provides an electronic device, a method for constructing a scoring model of retail outlets, a system and a computer readable medium. The method includes: crawling POI data of a predetermined map website by a crawler system; acquiring surrounding POI data based on a location of each retail outlet, and constructing POI relevant outlet features based on the surrounding POI data; acquiring surrounding LBS information based on the location of each retail outlet, and constructing client relevant features based on the surrounding LBS information; scoring each retail outlet based on a number of new clients increased in a predetermined time period and a revenue index; and constructing the scoring model by performing supervised learning of a preset classification algorithm model using the POI relevant outlet feature, the client relevant feature, and a score of the retail outlet.

Classes IPC  ?

  • G06Q 10/06 - Ressources, gestion de tâches, gestion d'hommes ou de projets, p.ex. organisation, planification, ordonnancement ou affectation de ressources en temps, hommes ou machines; Planification dans l'entreprise; Modèles organisationnels
  • G06Q 30/02 - Marketing, p.ex. études et analyse de marchés, prospection, promotions, publicité, établissement du profil des acheteurs, gestion ou fidélisation de clientèle; Estimation ou détermination des prix
  • G06F 16/951 - Indexation; Techniques d’exploration du Web
  • G06F 16/9537 - Recherche à dépendance spatiale ou temporelle, p.ex. requêtes spatio-temporelles
  • G06N 20/20 - Techniques d’ensemble en apprentissage automatique

76.

Method for generating model of sculpture of face with high meticulous, computing device, and non-transitory storage medium

      
Numéro d'application 16729154
Numéro de brevet 10991154
Statut Délivré - en vigueur
Date de dépôt 2019-12-27
Date de la première publication 2021-04-27
Date d'octroi 2021-04-27
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Li, Minghao
  • Miao, Jinghong
  • Gou, Yuchuan
  • Gong, Bo
  • Han, Mei

Abrégé

A method for generating a model for facial sculpture based on a generative adversarial network (GAN) includes training a predetermined GAN based on a three-dimensional (3D) face dataset of multiple 3D face images to obtain a curvature map generation model and training a predetermined image translation model based on dataset of multiple image pairs to obtain a height map generation model. Target 3D face data is received, and the target 3D face data is inputted into the curvature map generation model to generate a target curvature map, and the target curvature map is inputted to the height map generation model to generate a target height map. The target height map is performed a 3D reconstruction to obtain a facial sculpture model corresponding to the target 3D face data. A computing device using the method is also provided.

Classes IPC  ?

  • G06T 17/00 - Modélisation tridimensionnelle [3D] pour infographie
  • G06T 19/20 - Manipulation de modèles ou d'images tridimensionnels [3D] pour infographie Édition d'images tridimensionnelles [3D], p.ex. modification de formes ou de couleurs, alignement d'objets ou positionnements de parties
  • G06N 3/08 - Méthodes d'apprentissage
  • G06N 3/04 - Architecture, p.ex. topologie d'interconnexion

77.

METHOD AND DEVICE OF ANALYSIS BASED ON MODEL, AND COMPUTER READABLE STORAGE MEDIUM

      
Numéro d'application 16084242
Statut En instance
Date de dépôt 2017-08-31
Date de la première publication 2021-04-22
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s) Chen, Yiyun

Abrégé

The disclosure discloses a method and device of analysis based on a model, and a computer readable storage medium. The method includes: training various pre-determined models based on a preset number of customer information samples; combining the various trained models into a compound model according to a pre-determined combining rule, and after customer information to be analyzed is received, inputting the customer information to be analyzed into the compound model to output an analysis result. According to the disclosure, by the use of the compound model combined by the various models for analysis and prediction, the advantages of different models can be combined. Compared with a single model for prediction, the compound model effectively improves the accuracy of a prediction result.

Classes IPC  ?

  • G06Q 30/02 - Marketing, p.ex. études et analyse de marchés, prospection, promotions, publicité, établissement du profil des acheteurs, gestion ou fidélisation de clientèle; Estimation ou détermination des prix
  • G06F 30/10 - CAO géométrique
  • G06N 20/00 - Apprentissage automatique

78.

Enhanced medical images processing method and computing device

      
Numéro d'application 16710086
Numéro de brevet 10984530
Statut Délivré - en vigueur
Date de dépôt 2019-12-11
Date de la première publication 2021-04-20
Date d'octroi 2021-04-20
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Yao, Jiawen
  • Jin, Dakai
  • Lu, Le

Abrégé

An enhanced medical images processing method and a computing device includes: acquiring series of enhanced medical images and detecting a phase of each enhanced medical image in the series of enhanced medical images using a pre-trained 3D convolutional neural network model. A plurality of target enhanced medical images from the enhanced medical image are selected according to the phases. A plurality of interest images is obtained by identifying and segmenting an interest region in each of the plurality of target enhanced medical images, and finally registering the plurality of interest images. The registered images have clear phase markers and are all spatially aligned, allowing a subsequent doctor or clinician to directly use the registered interest images for diagnosis without the need to rescan the patient.

Classes IPC  ?

  • G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
  • G06T 7/00 - Analyse d'image
  • G06T 7/136 - Découpage; Détection de bords impliquant un seuillage
  • G06T 7/38 - Recalage de séquences d'images

79.

WEBPAGE DATA PROCESSING METHOD AND DEVICE, COMPUTER DEVICE AND COMPUTER STORAGE MEDIUM

      
Numéro d'application 16634010
Statut En instance
Date de dépôt 2018-02-23
Date de la première publication 2021-04-01
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD (Chine)
Inventeur(s) Zhang, Shuzi

Abrégé

A webpage data processing method and apparatus, a computer device and a storage medium, the method includes: acquiring first webpage data of a first webpage, querying a second webpage address associated with the first webpage data; acquiring a domain name of a website corresponding to a second webpage from the second webpage address, extracting a suffix of the domain name of the website corresponding to the second webpage; when the suffix of the domain name of the website corresponding to the second webpage is the same as a suffix of a pre-stored standard domain name, acquiring a network address corresponding to the standard domain name as a network address of the second webpage; accessing the second webpage according to the network address of the second webpage, and crawling second webpage data on the second webpage; respectively outputting the first webpage data and the second webpage data according to corresponding categories.

Classes IPC  ?

  • G06F 16/951 - Indexation; Techniques d’exploration du Web
  • H04L 29/12 - Dispositions, appareils, circuits ou systèmes non couverts par un seul des groupes caractérisés par le terminal de données
  • G06F 16/953 - Requêtes, p.ex. en utilisant des moteurs de recherche du Web
  • H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole

80.

Electronic device, method and system of identity verification and computer readable storage medium

      
Numéro d'application 16084233
Numéro de brevet 11068571
Statut Délivré - en vigueur
Date de dépôt 2017-08-31
Date de la première publication 2021-04-01
Date d'octroi 2021-07-20
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Wang, Jianzong
  • Guo, Hui
  • Xiao, Jing

Abrégé

An electronic device for identity verification includes a memory and a processor; the system of identity verification is stored in the memory, and executed by the processor to implement: after receiving current voice data of a target user, carrying out framing processing on the current voice data according to preset framing parameters to obtain multiple voice frames; extracting preset types of acoustic features in all the voice frames by using a predetermined filter, and generating multiple observed feature units corresponding to the current voice data according to the extracted acoustic features; pairwise coupling all the observed feature units with pre-stored observed feature units respectively to obtain multiple groups of coupled observed feature units; inputting the multiple groups of coupled observed feature units into a preset type of identity verification model generated by pre-training to carry out the identity verification on the target user.

Classes IPC  ?

  • G06F 21/32 - Authentification de l’utilisateur par données biométriques, p.ex. empreintes digitales, balayages de l’iris ou empreintes vocales
  • G06N 3/04 - Architecture, p.ex. topologie d'interconnexion
  • G10L 17/18 - Réseaux neuronaux artificiels; Approches connexionnistes
  • G10L 17/22 - Procédures interactives; Interfaces homme-machine
  • G10L 25/24 - Techniques d'analyses de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par le type de paramètres extraits les paramètres extraits étant le cepstre

81.

Exception stack information acquisition method and device and computer-readable storage medium

      
Numéro d'application 16088831
Numéro de brevet 11010227
Statut Délivré - en vigueur
Date de dépôt 2017-09-30
Date de la première publication 2021-04-01
Date d'octroi 2021-05-18
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Du, Yuan
  • Ye, Longfei

Abrégé

An exception stack information acquisition method, including: when a preset exception signal is sensed in a running process of a project, calling and executing an exception signal processing function to acquire first exception stack information of a native layer; reading second exception stack information recorded by an Application (APP) layer when the exception signal is sensed; and assembling the first exception stack information and the second exception stack information to obtain assembled information, then reporting the assembled information to a server, and aborting the project after reporting is completed.

Classes IPC  ?

  • G06F 11/00 - Détection d'erreurs; Correction d'erreurs; Contrôle de fonctionnement
  • G06F 11/07 - Réaction à l'apparition d'un défaut, p.ex. tolérance de certains défauts
  • G06F 11/34 - Enregistrement ou évaluation statistique de l'activité du calculateur, p.ex. des interruptions ou des opérations d'entrée–sortie
  • G06F 11/30 - Surveillance du fonctionnement

82.

CAR DAMAGE PICTURE ANGLE CORRECTION METHOD, ELECTRONIC DEVICE, AND READABLE STORAGE MEDIUM

      
Numéro d'application 16084993
Statut En instance
Date de dépôt 2017-09-30
Date de la première publication 2021-03-25
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Wang, Jianzong
  • Wang, Chenyu
  • Ma, Jin
  • Xiao, Jing

Abrégé

Disclosed are a car damage picture angle correction method, an electronic device, and a readable storage medium. The method includes: after receiving a car damage picture to be classified and identified, identifying a rotation category corresponding to the received car damage picture by using a pre-trained picture rotation category identification model; determining a rotation control parameter corresponding to the identified rotation category according to a pre-determined mapping relation between rotation categories and rotation control parameters, the rotation control parameter including a rotation angle and a rotation direction; and rotating the received car damage picture according to the determined rotation control parameter, so as to generate an angle-normal car damage picture. The disclosure can perform car damage picture angle correction more comprehensively and more effectively with no need to artificially perform angle identification on a car damage picture and to manually rotate the picture, thereby achieving a higher efficiency and accuracy.

Classes IPC  ?

  • G06Q 40/08 - Assurance, p.ex. analyse des risques ou pensions
  • G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques

83.

System and method of controlling obstacle avoidance of robot, robot and storage medium

      
Numéro d'application 16084231
Numéro de brevet 11059174
Statut Délivré - en vigueur
Date de dépôt 2017-06-30
Date de la première publication 2021-03-18
Date d'octroi 2021-07-13
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Zhou, Taotao
  • Zhou, Bao
  • Xiao, Jing

Abrégé

A system and method of controlling obstacle avoidance of a robot. The method includes acquiring current positioning data of the robot, and determining whether an obstacle, spaced from a current position at a distance shorter than a preset distance, exists in a path from the current position to a target position or not according to the current positioning data and position data of all obstacles in a predetermined moving region; if the obstacle exists, calculating the shortest distance between the robot and the obstacle according to the acquired positioning data, a predetermined 3D model of the robot and a predetermined 3D model of the obstacle; calculating a due movement direction of the current robot according to the acquired positioning data, the calculated shortest distance and the 3D model of the obstacle, and controlling a movement posture of the robot according to the calculated movement direction to avoid the obstacles.

Classes IPC  ?

  • G06F 17/00 - TRAITEMENT ÉLECTRIQUE DE DONNÉES NUMÉRIQUES Équipement ou méthodes de traitement de données ou de calcul numérique, spécialement adaptés à des fonctions spécifiques
  • B25J 9/16 - Commandes à programme
  • G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions
  • G06T 17/00 - Modélisation tridimensionnelle [3D] pour infographie

84.

Path planning system and method for robot, robot and medium

      
Numéro d'application 16084245
Numéro de brevet 11035684
Statut Délivré - en vigueur
Date de dépôt 2017-06-30
Date de la première publication 2021-03-18
Date d'octroi 2021-06-15
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Zhou, Chen
  • Zhou, Bao
  • Xiao, Jing

Abrégé

The disclosure discloses a path planning system and method for a robot, the robot and a medium. The method includes: preselecting, by the path planning system for the robot, one or more position points from paths on which the robot can move in a predetermined regional map as reference positioning points; and if an instruction of moving the robot from a first position point to a second position point is received, analyzing a path from the first position point to the second position point according to the set reference positioning points and according to a predetermined path analysis rule, and controlling the robot to move to the second position point on the basis of the analyzed path.

Classes IPC  ?

  • G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire
  • G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
  • G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions

85.

METHOD OF TRAINING RANDOM FOREST MODEL, ELECTRONIC DEVICE AND STORAGE MEDIUM

      
Numéro d'application 16084232
Statut En instance
Date de dépôt 2017-06-30
Date de la première publication 2021-03-18
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Jin, Ge
  • Xu, Liang
  • Xiao, Jing

Abrégé

A method of training a random forest model, an electronic device and a storage medium. The method of training the random forest model includes analyzing, by a system of controlling model training, whether model training conditions are met or not; if the model training conditions are met, determining whether reconstructive training needs to be carried out on the random forest model or not; if the reconstructive training needs to be carried out on the random forest model, carrying out the reconstructive training on the random forest model by using sample data; if the reconstructive training does not need to be carried out on the random forest model, carrying out corrective training on the random forest model by using the sample data.

Classes IPC  ?

  • G06N 20/20 - Techniques d’ensemble en apprentissage automatique
  • G06N 5/00 - Systèmes de calculateurs utilisant des modèles basés sur la connaissance
  • G06Q 10/10 - Bureautique, p.ex. gestion informatisée de courrier électronique ou logiciels de groupe; Gestion du temps, p.ex. calendriers, rappels, décompte de réunions ou de temps

86.

Speech recognition method, apparatus, and computer readable storage medium

      
Numéro d'application 16642371
Numéro de brevet 11081103
Statut Délivré - en vigueur
Date de dépôt 2017-11-28
Date de la première publication 2021-03-11
Date d'octroi 2021-08-03
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Liang, Hao
  • Cheng, Ning
  • Wang, Jianzong
  • Xiao, Jing

Abrégé

Disclosed are a speech recognition method, apparatus, computer device and storage medium. The method includes: performing a framing and an acoustic feature extraction of a speech-information-to-be-tested according to a default rule to obtain a frame-level speech feature sequence; dividing the frame-level speech feature sequence into n blocks sequentially; inputting all blocks into a preset bidirectional LSTM-RNN model parallelly to obtain an output result of the corresponding neuron in an output layer of the preset bidirectional LSTM-RNN model corresponding to the forward recognition result and backward recognition result of each block to obtain a speech recognition result of the speech-information-to-be-tested. The present application can improve the speech recognition effect significantly and reduce the time delay of the speech decoding effectively.

Classes IPC  ?

  • G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p.ex. dialogue homme-machine 
  • G10L 15/06 - Création de gabarits de référence; Entraînement des systèmes de reconnaissance de la parole, p.ex. adaptation aux caractéristiques de la voix du locuteur
  • G10L 15/02 - Extraction de caractéristiques pour la reconnaissance de la parole; Sélection d'unités de reconnaissance 
  • G10L 15/16 - Classement ou recherche de la parole utilisant des réseaux neuronaux artificiels
  • G10L 15/18 - Classement ou recherche de la parole utilisant une modélisation du langage naturel

87.

Network Anomaly Data Detection Method and Device as well as Computer Equipment and Storage Medium

      
Numéro d'application 16960031
Statut En instance
Date de dépôt 2018-05-28
Date de la première publication 2021-03-04
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s) Zhou, Shenglong

Abrégé

A network anomaly data detection method includes the following steps: receiving access request data transmitted by a client; searching historical access request data corresponding to a user session identifier in the access request data; acquiring a header character string of the access request data; performing word segmentation processing on the header character string according to a preset step length so as to obtain a word segmentation set; obtaining a word segmentation weight matrix according to the historical access request data and the word segmentation set; inputting the word segmentation weight matrix into an anomaly data detection model so as to obtain a data anomaly probability; and judging whether anomaly data exists in the header character string according to the data anomaly probability.

Classes IPC  ?

  • H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
  • G06F 16/903 - Requêtes
  • G06F 40/289 - Analyse syntagmatique, p.ex. techniques d’états finis ou regroupement
  • H04L 29/08 - Procédure de commande de la transmission, p.ex. procédure de commande du niveau de la liaison

88.

Medical image classification method and related device

      
Numéro d'application 16546627
Numéro de brevet 10997720
Statut Délivré - en vigueur
Date de dépôt 2019-08-21
Date de la première publication 2021-02-25
Date d'octroi 2021-05-04
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Zhou, Bo
  • Harrison, Adam Patrick
  • Yao, Jiawen
  • Lu, Le

Abrégé

A medical image classification method such as CT (or CAT) scans includes receiving the CT scan or medical image, inputting the medical image into an image classification model, which provides a cross entropy (CE) loss function and an aggregated cross entropy (ACE) loss function. According to the ACE loss function, image samples with generic label are used as input data during model training. The medical image can be classified by using the image classification model, and a classification of the medical image is thereby obtained. The present disclosure can classify indeterminate or general medical images and even unlabeled images and thus realize supervision of medical data. A device for applying the method is also provided.

Classes IPC  ?

  • G06T 7/00 - Analyse d'image
  • G16H 30/40 - TIC spécialement adaptées à la manipulation ou au traitement d’images médicales pour le traitement d’images médicales, p.ex. l’édition
  • G16H 30/20 - TIC spécialement adaptées à la manipulation ou au traitement d’images médicales pour la manipulation d’images médicales, p.ex. DICOM, HL7 ou PACS
  • G16H 10/60 - TIC spécialement adaptées à la manipulation ou au traitement de données médicales ou de soins de santé relatives aux patients pour des données spécifiques de patients, p.ex. pour des dossiers électroniques de patients
  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
  • G06T 7/11 - Découpage basé sur les zones
  • G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicales; TIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p.ex. basé sur des systèmes experts médicaux

89.

METHOD AND DEVICE FOR GENERATING MEDICAL REPORT

      
Numéro d'application 16633707
Statut En instance
Date de dépôt 2018-07-19
Date de la première publication 2021-02-25
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Wang, Chenyu
  • Wang, Jianzong
  • Xiao, Jing

Abrégé

The preset application is applied to the field of information processing technologies, and a method and a device for generating a medical report are provided. The method includes: receiving a medical image to be recognized; importing the medical image into a preset visual geometry group VGG neural network to acquire a visual feature vector and a keyword sequence of the medical image; importing the visual feature vector and the keyword sequence into a preset diagnostic item recognition model to determine diagnostic items corresponding to the medical image; constructing a paragraph for describing each of the diagnostic items respectively based on a diagnostic item extension model; generating a medical report for the medical image based on the paragraph, the keyword sequence and the diagnostic items.

Classes IPC  ?

  • G16H 15/00 - TIC spécialement adaptées aux rapports médicaux, p.ex. leur création ou leur transmission
  • G16H 30/20 - TIC spécialement adaptées à la manipulation ou au traitement d’images médicales pour la manipulation d’images médicales, p.ex. DICOM, HL7 ou PACS
  • G16H 30/40 - TIC spécialement adaptées à la manipulation ou au traitement d’images médicales pour le traitement d’images médicales, p.ex. l’édition
  • G06N 3/04 - Architecture, p.ex. topologie d'interconnexion

90.

Clinical target volume delineation method and electronic device

      
Numéro d'application 16546615
Numéro de brevet 11040219
Statut Délivré - en vigueur
Date de dépôt 2019-08-21
Date de la première publication 2021-02-25
Date d'octroi 2021-06-22
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Jin, Dakai
  • Guo, Dazhou
  • Lu, Le
  • Harrison, Adam Patrick

Abrégé

The present disclosure provides a clinical target volume delineation method and an electronic device. The method includes: receiving a radiotherapy computed tomography (RTCT) image; and obtaining a plurality of binary images by delineating a gross tumor volume (GTV), lymph nodes (LNs), and organs at risk (OARs) in the RTCT image. A SDMs for each of the binary images is calculated. The RTCT image and all the SDM are finally input into a clinical target volume (CTV) delineation model; and a CTV in the RTCT image is delineated by the CTV delineation model. An automatic delineation of the CTV of esophageal cancer are realized, a delineation efficiency is high and a delineation effect is good.

Classes IPC  ?

  • A61N 5/10 - Radiothérapie; Traitement aux rayons gamma; Traitement par irradiation de particules
  • G06T 7/00 - Analyse d'image
  • G16H 30/20 - TIC spécialement adaptées à la manipulation ou au traitement d’images médicales pour la manipulation d’images médicales, p.ex. DICOM, HL7 ou PACS
  • G16H 30/40 - TIC spécialement adaptées à la manipulation ou au traitement d’images médicales pour le traitement d’images médicales, p.ex. l’édition
  • A61B 6/03 - Tomographes assistés par ordinateur

91.

Fracture detection method, electronic device and storage medium

      
Numéro d'application 16546624
Numéro de brevet 10937143
Statut Délivré - en vigueur
Date de dépôt 2019-08-21
Date de la première publication 2021-02-25
Date d'octroi 2021-03-02
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Wang, Yirui
  • Lu, Le
  • Jin, Dakai
  • Harrison, Adam Patrick
  • Miao, Shun

Abrégé

A fracture detection method executed by an electronic device is provided. The fracture detection method includes obtaining a to-be-detected image; using a Fully Convolutional Networks (FCN) model to process the to-be-detected image to obtain a fracture probability map of the to-be-detected image; performing a maximum pooling process on the fracture probability map to obtain a first fracture probability; extracting Regions of Interests (ROIs) of the to-be-detected image based on the FCN model; inputting the ROIs into a classification model to obtain a second fracture probability; calculating a product of the first fracture probability and the second fracture probability as a probability of a fracture phenomenon in the to-be-detected image. The present disclosure combines the FCN model and the ROIs to realize an automatic fracture detection, and the accuracy is higher. A device employing the method is also disclosed.

Classes IPC  ?

  • G06T 7/00 - Analyse d'image
  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
  • G06N 20/00 - Apprentissage automatique
  • G06N 3/08 - Méthodes d'apprentissage

92.

Gross tumor volume segmentation method and computer device

      
Numéro d'application 16546604
Numéro de brevet 10929981
Statut Délivré - en vigueur
Date de dépôt 2019-08-21
Date de la première publication 2021-02-23
Date d'octroi 2021-02-23
Propriétaire Ping An Technology (Shenzhen) Co., Ltd. (Chine)
Inventeur(s)
  • Jin, Dakai
  • Guo, Dazhou
  • Lu, Le
  • Harrison, Adam Patrick

Abrégé

In a GTV segmentation method, a PET-CT image pair and an RTCT image of a human body are obtained. A PET image in the PET-CT image pair is aligned to the RTCT image to obtain an aligned PET image. A first PSNN performs a first GTV segmentation on the RTCT image to obtain a first segmentation image. The RTCT image and the aligned PET image are concatenated into a first concatenated image. A second PSNN performs a second GTV segmentation on the first concatenated image to obtain a second segmentation image. The RTCT image, the first segmentation image, and the second segmentation image are concatenated into a second concatenated image. A third PSNN performs a third GTV segmentation on the second concatenated image to obtain an object segmentation image.

Classes IPC  ?

  • G06T 7/174 - Découpage; Détection de bords impliquant l'utilisation de plusieurs images
  • G06T 7/30 - Détermination des paramètres de transformation pour l'alignement des images, c. à d. recalage des images
  • G06T 7/11 - Découpage basé sur les zones

93.

METHOD AND DEVICE FOR INVESTIGATING DATA, MOBILE TERMINAL, AND COMPUTER-READABLE STORAGE MEDIUM

      
Numéro d'application 16075020
Statut En instance
Date de dépôt 2017-06-23
Date de la première publication 2021-02-04
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Cai, Ning
  • Xiong, Wei
  • Jin, Yanhua
  • Fang, Xiao
  • Qiu, Yi

Abrégé

Disclosed is a method for investigating data, the method including: starting an investigation application program preinstalled on a mobile terminal, receiving an investigation request in a display interface of the investigation application program, and determining whether a corresponding initiator of the investigation request is a predetermined investigating role; receiving an assignment instruction to assign the investigation task when the corresponding initiator of the investigation request is the predetermined investigating role and a corresponding investigation task of the investigation request is a predetermined task; and performing a corresponding transfer or assignment of the investigation task after determining the investigation task needs to be transferred or assigned, when the corresponding initiator of the investigation request is the predetermined investigating role and the corresponding investigation task of the investigation request is not the predetermined task. Also disclosed are a device, a mobile terminal, and a computer-readable storage medium for investigating data.

Classes IPC  ?

  • G06Q 10/10 - Bureautique, p.ex. gestion informatisée de courrier électronique ou logiciels de groupe; Gestion du temps, p.ex. calendriers, rappels, décompte de réunions ou de temps
  • G06Q 10/06 - Ressources, gestion de tâches, gestion d'hommes ou de projets, p.ex. organisation, planification, ordonnancement ou affectation de ressources en temps, hommes ou machines; Planification dans l'entreprise; Modèles organisationnels
  • G06Q 40/08 - Assurance, p.ex. analyse des risques ou pensions

94.

Methods and devices for optimizing load balancing based on cloud monitoring

      
Numéro d'application 16075327
Numéro de brevet 10992581
Statut Délivré - en vigueur
Date de dépôt 2017-10-24
Date de la première publication 2021-02-04
Date d'octroi 2021-04-27
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Kuang, Guangcai
  • Yi, Renjie

Abrégé

Disclosed is a method and a device for optimizing load balancing based on cloud monitoring that relate to loading balancing and that can improve the primary/backup Availability Zone (AZ) switchover efficiency of an load balancing instance by intelligently switching the preferences of load balancing devices. The method includes: obtaining statistics on traffic distribution within a controlled area of a load balancing system, statistics on backend servers within a plurality of AZs of the load balancing system, and monitored network quality of the AZs; determining an AZ suitable to serve as a corresponding primary AZ of a load balancing instance based on the traffic distribution statistics, the backend server statistics, and the monitored network quality; and performing a primary AZ switchover of the load balancing instance based on the determined result. The present application is intended for the optimizing of load balancing.

Classes IPC  ?

  • H04L 12/26 - Dispositions de surveillance; Dispositions de test
  • H04L 12/803 - Commande de flux ou commande de congestion Équilibrage de charge, p.ex. répartition du trafic entre multiples liens
  • H04L 29/08 - Procédure de commande de la transmission, p.ex. procédure de commande du niveau de la liaison

95.

Method and device for identifying a user interest, and computer-readable storage medium

      
Numéro d'application 16318818
Numéro de brevet 10977447
Statut Délivré - en vigueur
Date de dépôt 2017-09-28
Date de la première publication 2021-02-04
Date d'octroi 2021-04-13
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Wang, Jianzong
  • Huang, Zhangcheng
  • Wu, Tianbo
  • Xiao, Jing

Abrégé

Disclosed is a method for identifying a user interest, including: obtaining training samples and test samples, the training samples being obtained by manually labeling after the corresponding topic models have been trained based on text data; extracting characteristics of the training samples and of the test samples, and computing optimal model parameters of a logistic regression model by an iterative algorithm based on the characteristics of the training samples; evaluating the logistic regression model based on the characteristics of the test samples and an area AUC under an ROC curve to train and obtain a first theme classifier; determining a theme to which the text data belongs using the first theme classifier, computing a score of the theme to which the text data belongs based on the logistic regression model, and computing a confidence score of the user being interested in the theme according to a second preset algorithm. Further disclosed are a device for identifying a user interest and a computer-readable storage medium.

Classes IPC  ?

96.

Data access authority management method, apparatus, terminal device and storage medium

      
Numéro d'application 16098129
Numéro de brevet 11093631
Statut Délivré - en vigueur
Date de dépôt 2018-02-28
Date de la première publication 2020-11-12
Date d'octroi 2021-08-17
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Tan, Zhijie
  • Liang, Yongjian
  • Zhang, Chuan

Abrégé

This application discloses a data access authority management method, apparatus, terminal device and storage medium. The data access authority management method comprises obtaining report metadata in Tableau, the report metadata comprises report ID; creating folder data in Portal platform, the folder data comprises at least one folder, and the folder comprises folder ID; creating a correlation relationship between the report ID and the folder ID in Portal platform; obtaining user class authority configuration request entered by user, the user class authority configuration request comprises user class ID and target folder ID; performing user class authority configuration based on the user class authority configuration request in Portal platform, so as to enable the user class corresponding to the user class ID to have access authority to access report metadata which is corresponded to the report ID corresponding to the target folder ID.

Classes IPC  ?

  • G08B 23/00 - Alarmes réagissant à des conditions indésirables ou anormales, non spécifiées
  • G06F 12/16 - Protection contre la perte de contenus de mémoire
  • G06F 12/14 - Protection contre l'utilisation non autorisée de mémoire
  • G06F 11/00 - Détection d'erreurs; Correction d'erreurs; Contrôle de fonctionnement
  • G06F 21/62 - Protection de l’accès à des données via une plate-forme, p.ex. par clés ou règles de contrôle de l’accès
  • G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
  • G06F 16/22 - Indexation; Structures de données à cet effet; Structures de stockage
  • G06F 16/28 - Bases de données caractérisées par leurs modèles, p.ex. des modèles relationnels ou objet
  • G06F 21/31 - Authentification de l’utilisateur

97.

Data transmission method, apparatus, terminal device, and medium

      
Numéro d'application 16088807
Numéro de brevet 11146571
Statut Délivré - en vigueur
Date de dépôt 2018-02-26
Date de la première publication 2020-10-01
Date d'octroi 2021-10-12
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Tian, Zhengwei
  • Feng, Chao
  • Xue, Yan

Abrégé

A data transmission method, including: acquiring business data to be uploaded which arc sent from a plurality of organizations; respectively checking whether or not the business data to be uploaded arc complete; acquiring business identifiers carried in the business data to be uploaded from organizations whose data are reviewed to be complete; performing first grouping on the business data to be uploaded from the organizations whose data arc reviewed to be complete, in accordance with the business identifiers; determining data size of the business data to be uploaded and acquiring a data size of each group after the first grouping; performing second grouping on a grouping result of the first grouping; and uploading the business data to be uploaded from the organizations whose data are reviewed to be complete in accordance with a grouping result of the second grouping.

Classes IPC  ?

  • H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
  • G06F 16/901 - Indexation; Structures de données à cet effet; Structures de stockage
  • G06Q 30/02 - Marketing, p.ex. études et analyse de marchés, prospection, promotions, publicité, établissement du profil des acheteurs, gestion ou fidélisation de clientèle; Estimation ou détermination des prix

98.

DATA SOURCE-BASED SERVICE CUSTOMIZING DEVICE, METHOD AND SYSTEM, AND STORAGE MEDIUM

      
Numéro d'application 16084565
Statut En instance
Date de dépôt 2017-06-30
Date de la première publication 2020-09-24
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Wang, Jianzong
  • Huang, Zhangcheng
  • Wu, Tianbo
  • Xiao, Jing

Abrégé

The disclosure relates to a data source-based service customizing device, method and system, and a computer readable storage medium. The data source-based service customizing device includes: a memory, a processor and the data source-based service customizing system stored on the memory and operated on the processor. The data source-based service customizing system is executed by the processor to implement the following steps: acquiring user generated contents in various predetermined data sources; recognizing the user generated contents by using a user group label recognition model generated by pre-training to recognize user group labels corresponding to the various data sources; determining group services corresponding to the various data sources according to a predetermined mapping relation between the user group labels and the group services, and sending the various data sources and the corresponding group services to a predetermined terminal to perform group service customization on the various data sources.

Classes IPC  ?

  • G06Q 10/04 - Prévision ou optimisation, p.ex. programmation linéaire, "problème du voyageur de commerce" ou "problème d'optimisation des stocks"
  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
  • G06N 20/00 - Apprentissage automatique
  • G06N 7/00 - Systèmes de calculateurs basés sur des modèles mathématiques spécifiques

99.

Routing configuration method of view files, storage medium, terminal device and apparatus

      
Numéro d'application 16088061
Numéro de brevet 10887171
Statut Délivré - en vigueur
Date de dépôt 2018-02-13
Date de la première publication 2020-09-24
Date d'octroi 2021-01-05
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s) Jin, Mengjie

Abrégé

The present application discloses a routing configuration method of view files, a computer readable storage medium, a terminal device and an apparatus, which aims at solving a problem that an efficiency of manually configuring routing information of view file is low and routing configuration errors are prone to occur. The routing configuration method comprises: determining a target single page application; detecting whether there exists an update in a view file of the target single page application; determining an updated target view file if there is the update for the view file of the target single page application; acquiring update state information of the target view file; and updating routing configuration information in a routing configuration file of the target single page application according to the update state information.

Classes IPC  ?

  • G06F 15/173 - Communication entre processeurs utilisant un réseau d'interconnexion, p.ex. matriciel, de réarrangement, pyramidal, en étoile ou ramifié
  • H04L 12/24 - Dispositions pour la maintenance ou la gestion
  • H04L 29/08 - Procédure de commande de la transmission, p.ex. procédure de commande du niveau de la liaison

100.

METHOD AND APPARATUS FOR TRAINING SEMANTIC SEGMENTATION MODEL, COMPUTER DEVICE, AND STORAGE MEDIUM

      
Numéro d'application 16759383
Statut En instance
Date de dépôt 2018-07-13
Date de la première publication 2020-09-17
Propriétaire PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (Chine)
Inventeur(s)
  • Wang, Jianzong
  • Wang, Chenyu
  • Ma, Jin
  • Xiao, Jing

Abrégé

A method and apparatus for training a semantic segmentation model, a computer device, and a storage medium are described herein. The method includes: constructing a training sample set; inputting the training sample set into a deep network model for training; inputting the training sample set into a weight transfer function for training to obtain a bounding box prediction mask parameter; and constructing a semantic segmentation model.

Classes IPC  ?

  • G06T 7/10 - Découpage; Détection de bords
  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
  • G06N 3/08 - Méthodes d'apprentissage
  • G06N 3/06 - Réalisation physique, c. à d. mise en oeuvre matérielle de réseaux neuronaux, de neurones ou de parties de neurones
  1     2        Prochaine page