Ping An Technology (Shenzhen) Co., LTD.

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G06K 9/62 - Methods or arrangements for recognition using electronic means 35
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints 26
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1.

DEVICE AND METHOD FOR GLAUCOMA AUXILIARY DIAGNOSIS, AND STORAGE MEDIUM

      
Application Number 17539860
Status Pending
Filing Date 2021-12-01
First Publication Date 2022-04-28
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Liu, Yang
  • Zhang, Chengfen
  • Lv, Bin
  • Lv, Chuanfeng

Abstract

A device and method for glaucoma auxiliary diagnosis, and a non-transitory storage medium are provided. The device includes an obtaining unit and a processing unit. The obtaining unit is configured to obtain a color fundus image of a patient. The processing unit is configured to perform feature extraction on the color fundus image to obtain a first feature map. The processing unit is further configured to perform image segmentation on the color fundus image according to the first feature map to obtain an optic disc image in the color fundus image, where the optic disc image corresponds to an optic disc area in the color fundus image. The processing unit is further configured to perform feature extraction on the optic disc image and the color fundus image according to the first feature map to obtain a probability that the patient has glaucoma.

IPC Classes  ?

  • G06T 7/143 - Segmentation; Edge detection involving probabilistic approaches, e.g. Markov random field [MRF] modelling
  • G06T 7/194 - Segmentation; Edge detection involving foreground-background segmentation

2.

KNOWLEDGE GRAPH-BASED CASE RETRIEVAL METHOD, DEVICE AND EQUIPMENT, AND STORAGE MEDIUM

      
Application Number 17271209
Status Pending
Filing Date 2020-05-29
First Publication Date 2022-04-21
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Zhang, Xuechen
  • Liu, Jiawei
  • Yu, Xiuming
  • Chen, Chen
  • Li, Ke
  • Wang, Wei

Abstract

This application discloses a knowledge graph-based case retrieval method, device and equipment, and a storage medium. The method includes: constructing a legal case knowledge graph based on text information; performing random-walk sampling on node set data constructed based on the legal case knowledge graph, so as to obtain a plurality of pieces of sequence data; training a model by using a word2vec algorithm based on the plurality of pieces of sequence data, so as to obtain an updated target model; obtaining target text information, and analyzing the target text information by using the target model, so as to construct a to-be-retrieved knowledge graph; retrieving the legal case knowledge graph based on the to-be-retrieved knowledge graph, so as to obtain case information associated with the to-be-retrieved knowledge graph; and obtaining outputted case information based on a first similarity and a second similarity of the case information.

IPC Classes  ?

3.

METHOD, DEVICE, AND EQUIPMENT FOR USER GROUPING, AND COMPUTER-READABLE STORAGE MEDIUM

      
Application Number 17533471
Status Pending
Filing Date 2021-11-23
First Publication Date 2022-04-14
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Chen, Tiange
  • Zhang, Yuan

Abstract

A method, device, equipment for user grouping, and a non-transitory computer-readable storage medium are provided, which are applicable to the field of medical technology. The method includes the following. Net benefits of multiple users in a target project are obtained. According to the net benefits of the multiple users in the target project and a solution of the target project, a net-benefit coefficient corresponding to the solution is determined. For each grouping variable of the target project, a fluctuation value corresponding to the grouping variable is determined according to the net-benefit coefficient. According to a grouping variable with the largest fluctuation value, the multiple users are divided into multiple user groups. For each user group obtained by division, users in the user group are divided according to a fluctuation value corresponding to each grouping variable of the target project, until a user group meeting a preset condition is obtained.

IPC Classes  ?

  • G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
  • G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
  • G16H 10/20 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
  • G06Q 10/06 - Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models

4.

DATA DETECTION METHOD AND DEVICE, COMPUTER EQUIPMENT AND STORAGE MEDIUM

      
Application Number 17264311
Status Pending
Filing Date 2020-06-29
First Publication Date 2022-04-14
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor Huang, Jinlun

Abstract

Disclosed are a data detection method and device, a computer equipment, and a storage medium. The method includes: obtaining a designated identification picture including a human face; correcting the designated identification picture to be placed in a preset standard posture to obtain an intermediate picture; inputting the intermediate picture into a preset face feature point detection model to obtain multiple face feature points; calculating a cluster center position of the face feature points, and generating a minimum bounding rectangle of the face feature points; retrieving a standard identification picture from a preset database; scaling the standard identification picture in proportion to obtain a scaled picture; overlapping a reference center position in the scaled picture and a cluster center position in the intermediate picture, so as to obtain an overlapping part in the intermediate picture; and marking the overlapping part as an identification body of the designated identification picture.

IPC Classes  ?

  • G06V 40/16 - Human faces, e.g. facial parts, sketches or expressions
  • G06T 5/50 - Image enhancement or restoration by the use of more than one image, e.g. averaging, subtraction
  • G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
  • G06V 10/762 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using clustering, e.g. of similar faces in social networks

5.

METHOD AND DEVICE FOR NEURAL NETWORK-BASED OPTICAL COHERENCE TOMOGRAPHY (OCT) IMAGE LESION DETECTION, AND MEDIUM

      
Application Number 17551460
Status Pending
Filing Date 2021-12-15
First Publication Date 2022-04-07
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Fan, Dongyi
  • Wang, Lilong
  • Wang, Rui
  • Wang, Guanzheng
  • Lv, Chuanfeng

Abstract

A method and device for neural network-based optical coherence tomography (OCT) image lesion detection, and a medium are provided. The method includes the following. An OCT image is obtained. The OCT image is inputted into a lesion-detection network model. A position, a category score, and a positive score of each lesion box in the OCT image are outputted through the lesion-detection network model. A lesion detection result of the OCT image is obtained according to the position, the category score, and the positive score of each lesion box. The lesion-detection network model includes a category detection branch configured to obtain, for each of the anchor boxes, a position and a category score of the anchor box, and a lesion positive score regression branch configured to obtain, for each of the anchor boxes, a positive score of whether the anchor box belongs to a lesion, to reflect severity of lesion positive.

IPC Classes  ?

  • G06T 7/00 - Image analysis
  • G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
  • G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

6.

METHOD FOR DRUG CLASSIFICATION, TERMINAL DEVICE, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM

      
Application Number 17539794
Status Pending
Filing Date 2021-12-01
First Publication Date 2022-03-31
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Wang, Jun
  • Li, Pengyong

Abstract

A method for drug classification, a terminal device, and a non-transitory computer-readable storage medium are provided. An attribute feature vector of each of n atoms in a drug molecule to be detected and an attribute feature vector of a virtual atom are obtained. An adjacency matrix is constructed according to a connection relationship between the virtual atom and each of the n atoms and between the n atoms. An atom attribute feature matrix is constructed according to the attribute feature vector of each atom. The adjacency matrix and the atom attribute feature matrix are inputted into a graph neural network to determine a transfer feature matrix of the n atoms and the virtual atom. A molecular feature vector corresponding to the drug molecule to be detected is determined according to the transfer feature matrix. The molecular feature vector is inputted into a classifier to output a drug category.

IPC Classes  ?

  • G16C 20/20 - Identification of molecular entities, parts thereof or of chemical compositions
  • G16H 70/40 - ICT specially adapted for the handling or processing of medical references relating to drugs, e.g. their side effects or intended usage
  • G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
  • G06N 3/04 - Architecture, e.g. interconnection topology
  • G16C 20/70 - Machine learning, data mining or chemometrics

7.

METHOD FOR MODEL DEPLOYMENT, TERMINAL DEVICE, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM

      
Application Number 17530801
Status Pending
Filing Date 2021-11-19
First Publication Date 2022-03-10
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Tang, Yijun
  • Sun, Lan
  • Fan, Liyang

Abstract

A method for model deployment, a terminal device, and a non-transitory computer-readable storage medium are provided. The method includes the following. A to-be-deployed model and an input/output description file of the to-be-deployed model are obtained. Output verification is performed on the to-be-deployed model based on the input/output description file. If the output verification of the to-be-deployed model passes, an inference service resource is determined from multiple running environments and the inference service resource is allocated to the to-be-deployed model. An inference parameter value of executing an inference service by the to-be-deployed model based on the inference service resource is determined. A resource configuration file and an inference service interface of the to-be-deployed model are generated according to the inference service resource, if the inference parameter value is greater than or equal to a preset inference parameter threshold.

IPC Classes  ?

  • G06N 20/00 - Machine learning
  • G06F 16/11 - File system administration, e.g. details of archiving or snapshots

8.

METHOD AND APPARATUS FOR MAMMOGRAPHIC MULTI-VIEW MASS IDENTIFICATION

      
Application Number 17165087
Status Pending
Filing Date 2021-02-02
First Publication Date 2022-03-03
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Yang, Zhicheng
  • Cao, Zhenjie
  • Zhang, Yanbo
  • Chang, Peng
  • Han, Mei
  • Xiao, Jing

Abstract

A method, applied to an apparatus for mammographic multi-view mass identification, includes receiving a main image, a first auxiliary image, and a second auxiliary image. The main image and the first auxiliary image are images of a breast of a person, and the second auxiliary image is an image of another breast of the person. The method further includes detecting the nipple location based on the main image and the first auxiliary image; generating a first probability map of the main image based on the main image, the first auxiliary image, and the nipple location; generating a second probability map of the main image based on the main image, the second auxiliary image, and the nipple location; and generating and outputting a fused probability map based on the first probability map and the second probability map.

IPC Classes  ?

  • G06T 7/00 - Image analysis
  • G06K 9/32 - Aligning or centering of the image pick-up or image-field
  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06T 7/11 - Region-based segmentation
  • G06T 7/30 - Determination of transform parameters for the alignment of images, i.e. image registration

9.

METHOD AND DEVICE FOR IMAGE GENERATION AND COLORIZATION

      
Application Number 17122680
Status Pending
Filing Date 2020-12-15
First Publication Date 2022-02-10
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Gou, Yuchuan
  • Li, Minghao
  • Gong, Bo
  • Han, Mei

Abstract

A method and device for image generation and colorization are provided. The method includes: displaying a drawing board interface; obtaining semantic labels of an image to be generated based on user input on the drawing board interface, each semantic label indicating a content of a region in the image to be generated; obtaining a color feature of the image to be generated; and automatically generating the image using a generative adversarial network (GAN) model according to the semantic labels and the color feature. The color feature is a latent vector input to the GAN model.

IPC Classes  ?

  • G06T 11/00 - 2D [Two Dimensional] image generation
  • G06K 9/46 - Extraction of features or characteristics of the image
  • G06K 9/72 - Methods or arrangements for recognition using electronic means using context analysis based on the provisionally recognised identity of a number of successive patterns, e.g. a word
  • G06N 3/04 - Architecture, e.g. interconnection topology

10.

USER-GUIDED DOMAIN ADAPTATION FOR RAPID ANNOTATION FROM USER INTERACTIONS FOR PATHOLOGICAL ORGAN SEGMENTATION

      
Application Number 17138251
Status Pending
Filing Date 2020-12-30
First Publication Date 2022-02-10
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Harrison, Adam P.
  • Raju, Ashwin

Abstract

The present disclosure provides a computer-implemented method, a device, and a computer program product using a user-guided domain adaptation (UGDA) architecture. The method includes training a combined model using a source image dataset by minimizing a supervised loss of the combined model to obtain first sharing weights for a first FCN and second sharing weights for a second FCN; training a discriminator by inputting extreme-point/mask prediction pairs for each of the source image dataset and a target image dataset and by minimizing a discriminator loss to obtain discriminator weights; and finetuning the combined model by predicting extreme-point/mask prediction pairs for the target image dataset to fool the discriminator by matching a distribution of the extreme-point/mask prediction pairs for the target image dataset with a distribution of the extreme-point/mask prediction pairs for the source image dataset.

IPC Classes  ?

  • G06T 7/00 - Image analysis
  • G06T 7/33 - Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods
  • G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

11.

METHOD AND DEVICE FOR TEXT-BASED IMAGE GENERATION

      
Application Number 17344484
Status Pending
Filing Date 2021-06-10
First Publication Date 2022-01-06
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Gou, Yuchuan
  • Wu, Qiancheng
  • Li, Minghao
  • Gong, Bo
  • Han, Mei

Abstract

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.

IPC Classes  ?

  • G06T 11/00 - 2D [Two Dimensional] image generation
  • G06F 40/126 - Character encoding
  • G06F 40/279 - Recognition of textual entities
  • G06N 3/02 - Computer systems based on biological models using neural network models

12.

METHOD AND SYSTEM FOR RESPONDING TO VIDEO CALL SERVICE

      
Application Number 16644456
Status Pending
Filing Date 2018-07-27
First Publication Date 2021-12-02
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Cheng, Huilin
  • Liu, Dechao

Abstract

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.

IPC Classes  ?

  • H04L 29/06 - Communication control; Communication processing characterised by a protocol
  • H04L 29/08 - Transmission control procedure, e.g. data link level control procedure
  • H04W 24/02 - Arrangements for optimising operational condition

13.

TARGET CUSTOMER IDENTIFICATION METHOD AND DEVICE, ELECTRONIC DEVICE AND MEDIUM

      
Application Number 16316028
Status Pending
Filing Date 2017-09-29
First Publication Date 2021-11-25
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Li, Fang
  • Wang, Jianming
  • Xiao, Jing

Abstract

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.

IPC Classes  ?

  • G06Q 30/02 - Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
  • G06Q 10/06 - Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
  • G06N 20/20 - Ensemble learning

14.

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

      
Application Number 17110859
Status Pending
Filing Date 2020-12-03
First Publication Date 2021-11-25
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Liu, Fengze P.
  • Cai, Jinzheng
  • Huo, Yuankai
  • Lu, Le
  • Harrison, Adam P.

Abstract

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.

IPC Classes  ?

15.

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

      
Application Number 16315254
Status Pending
Filing Date 2018-02-27
First Publication Date 2021-10-28
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor Lu, Zheng

Abstract

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.

IPC Classes  ?

  • G06F 9/451 - Execution arrangements for user interfaces
  • G06F 9/445 - Program loading or initiating
  • G06F 8/38 - Creation or generation of source code for implementing user interfaces
  • G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
  • G06F 3/0482 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance interaction with lists of selectable items, e.g. menus
  • G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object or an image, setting a parameter value or selecting a range

16.

Exclusive agent pool allocation method, electronic device, and computer readable storage medium

      
Application Number 16315255
Grant Number 11272059
Status In Force
Filing Date 2018-02-12
First Publication Date 2021-10-28
Grant Date 2022-03-08
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor Niu, Hua

Abstract

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; 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.

IPC Classes  ?

  • H04M 3/523 - Centralised call answering arrangements requiring operator intervention with call distribution or queuing
  • G06Q 10/06 - Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
  • H04M 3/51 - Centralised call answering arrangements requiring operator intervention

17.

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

      
Application Number 17263899
Status Pending
Filing Date 2019-11-12
First Publication Date 2021-10-21
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Wang, Jianzong
  • Huang, Zhangcheng

Abstract

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.

IPC Classes  ?

  • G06Q 40/08 - Insurance, e.g. risk analysis or pensions
  • G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check of credit lines or negative lists
  • G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
  • G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
  • G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
  • G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
  • G06F 16/901 - Indexing; Data structures therefor; Storage structures
  • G06F 16/906 - Clustering; Classification

18.

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

      
Application Number 16328200
Status Pending
Filing Date 2018-01-31
First Publication Date 2021-10-21
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor Cai, Jinsheng

Abstract

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.

IPC Classes  ?

  • G06F 40/263 - Language identification
  • G06F 40/242 - Dictionaries
  • G06T 5/00 - Image enhancement or restoration
  • G06K 9/46 - Extraction of features or characteristics of the image
  • G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
  • G06K 9/32 - Aligning or centering of the image pick-up or image-field

19.

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

      
Application Number 16338957
Status Pending
Filing Date 2018-02-27
First Publication Date 2021-10-07
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor Qiu, Bei

Abstract

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.

IPC Classes  ?

  • G06F 21/32 - User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
  • G06F 21/36 - User authentication by graphic or iconic representation
  • G10L 17/06 - Decision making techniques; Pattern matching strategies
  • H04W 4/12 - Messaging; Mailboxes; Announcements

20.

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

      
Application Number 17264312
Status Pending
Filing Date 2019-11-13
First Publication Date 2021-10-07
Owner PING AN TECHNOLOGY(SHENZHEN)CO.,LTD. (China)
Inventor
  • Wang, Yiwen
  • Wang, Jianzong

Abstract

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.

IPC Classes  ?

  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06T 7/12 - Edge-based segmentation
  • G06T 7/194 - Segmentation; Edge detection involving foreground-background segmentation
  • G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
  • G06K 9/46 - Extraction of features or characteristics of the image
  • G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
  • G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis

21.

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

      
Application Number 17266587
Status Pending
Filing Date 2019-11-12
First Publication Date 2021-10-07
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Zhao, Moyan
  • Wang, Hongwei

Abstract

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.

IPC Classes  ?

  • G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
  • G06K 9/62 - Methods or arrangements for recognition using electronic means

22.

Systems and methods for tumor characterization

      
Application Number 16836855
Grant Number 11282193
Status In Force
Filing Date 2020-03-31
First Publication Date 2021-09-30
Grant Date 2022-03-22
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Harrison, Adam P.
  • Huo, Yuankai
  • Cai, Jinzheng
  • Raju, Ashwin
  • Yan, Ke
  • Lu, Le

Abstract

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.

IPC Classes  ?

  • G06T 7/00 - Image analysis
  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06T 7/49 - Analysis of texture based on structural texture description, e.g. using primitives or placement rules
  • A61B 6/03 - Computerised tomographs
  • A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment

23.

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

      
Application Number 17264299
Status Pending
Filing Date 2019-08-30
First Publication Date 2021-09-23
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Jia, Wenxiao
  • Tan, Kewei
  • Li, Xiang
  • Xie, Guotong

Abstract

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.

IPC Classes  ?

  • G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders

24.

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

      
Application Number 17264307
Status Pending
Filing Date 2019-05-30
First Publication Date 2021-09-23
Owner PING AN TECHNOLOGY(SHENZHEN)CO.,LTD. (China)
Inventor
  • Guo, Yan
  • Lv, Bin
  • Lv, Chuanfeng
  • Xie, Guotong

Abstract

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.

IPC Classes  ?

25.

DATA STORAGE METHOD AND APPARATUS, STORAGE MEDIUM AND COMPUTER DEVICE

      
Application Number 17264321
Status Pending
Filing Date 2018-10-21
First Publication Date 2021-09-23
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Sun, Cheng
  • Ye, Junfeng
  • Lai, Yunhui
  • Luo, Xianxian
  • Long, Juegang

Abstract

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.

IPC Classes  ?

  • G06F 3/06 - Digital input from, or digital output to, record carriers

26.

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

      
Application Number 17266187
Status Pending
Filing Date 2018-12-24
First Publication Date 2021-09-23
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor Yang, Guoqing

Abstract

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.

IPC Classes  ?

  • G06T 7/246 - Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
  • G06T 7/70 - Determining position or orientation of objects or cameras
  • G06N 3/08 - Learning methods

27.

METHOD AND SYSTEM FOR IMAGE SEGMENTATION

      
Application Number 17128993
Status Pending
Filing Date 2020-12-21
First Publication Date 2021-09-16
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Zheng, Kang
  • Lu, Yuhang
  • Li, Weijian
  • Wang, Yirui
  • Harrison, Adam P
  • Lu, Le
  • Miao, Shun

Abstract

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.

IPC Classes  ?

28.

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

      
Application Number 16095344
Status Pending
Filing Date 2018-02-26
First Publication Date 2021-09-02
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Yu, Liangling
  • Dai, Congjian
  • Fang, Huangwei
  • Ye, Weiwei
  • Li, Xiaohua

Abstract

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.

IPC Classes  ?

  • G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
  • H04L 12/26 - Monitoring arrangements; Testing arrangements

29.

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

      
Application Number 16097872
Grant Number 11163851
Status In Force
Filing Date 2017-11-23
First Publication Date 2021-08-19
Grant Date 2021-11-02
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor Shi, Guiling

Abstract

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.

IPC Classes  ?

  • G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions
  • G06F 16/958 - Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
  • G06F 16/901 - Indexing; Data structures therefor; Storage structures
  • G06F 16/903 - Querying
  • G06F 16/957 - Browsing optimisation, e.g. caching or content distillation

30.

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

      
Application Number 17089257
Status Pending
Filing Date 2020-11-04
First Publication Date 2021-08-19
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Harrison, Adam P.
  • Raju, Ashwin
  • Huo, Yuankai
  • Cai, Jinzheng
  • Lu, Le

Abstract

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.

IPC Classes  ?

  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06T 7/00 - Image analysis
  • G06T 7/11 - Region-based segmentation
  • G06K 9/46 - Extraction of features or characteristics of the image
  • G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

31.

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

      
Application Number 17165665
Status Pending
Filing Date 2021-02-02
First Publication Date 2021-08-19
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Chen, Xianxian
  • Ruan, Xiaowen
  • Xu, Liang

Abstract

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.

IPC Classes  ?

  • G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
  • G06N 20/00 - Machine learning
  • G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
  • G16H 70/20 - ICT specially adapted for the handling or processing of medical references relating to practices or guidelines
  • G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
  • G06F 40/30 - Semantic analysis
  • G06F 40/284 - Lexical analysis, e.g. tokenisation or collocates

32.

Blockchain system and blockchain transaction data processing method based on ethereum

      
Application Number 16097876
Grant Number 11294888
Status In Force
Filing Date 2017-11-23
First Publication Date 2021-08-19
Grant Date 2022-04-05
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Wu, Yiming
  • Gu, Qingshan

Abstract

The present application relates to a blockchain system based on Ethereum, including a master node configured to receive a transaction request transmitted by a client terminal, perform transaction processing by calling a smart contract deployed in a consortium blockchain according to the transaction request to obtain transaction data; and use the transaction data to generate a block, and broadcast the block is to the plurality of backup nodes; backup node configured to receive the block and verify the transaction data of the block; the master node is further configured to generate a first-stage certificate using complete block information, and transmit the first-stage certificate to the plurality of backup nodes; the backup node is further configured to respectively generate a second-stage certificate and a third-stage certificate according to a block hash value in the first-stage certificate, and the second-stage certificate and the third-stage certificate are respectively used to negotiate on the block to obtain a negotiation result; and when the block verification is passed and the negotiation result is a successful negotiation, the master node and the plurality of backup nodes are configured respectively to add the block to the copy of the local consortium blockchain.

IPC Classes  ?

  • G06F 16/23 - Updating
  • G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
  • H04L 9/32 - Arrangements for secret or secure communication including means for verifying the identity or authority of a user of the system
  • H04L 29/08 - Transmission control procedure, e.g. data link level control procedure
  • H04L 12/24 - Arrangements for maintenance or administration
  • H04L 29/06 - Communication control; Communication processing characterised by a protocol
  • H04L 67/60 - Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
  • H04L 41/0663 - Performing the actions predefined by failover planning, e.g. switching to standby network elements

33.

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

      
Application Number 16301429
Status Pending
Filing Date 2018-02-12
First Publication Date 2021-07-29
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor Wang, Haiping

Abstract

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.

IPC Classes  ?

  • G06Q 10/10 - Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
  • G06Q 30/00 - Commerce, e.g. shopping or e-commerce
  • G06F 16/22 - Indexing; Data structures therefor; Storage structures
  • G06F 16/23 - Updating
  • G06F 16/245 - Query processing
  • G06F 7/08 - Sorting, i.e. grouping record carriers in numerical or other ordered sequence according to the classification of at least some of the information they carry

34.

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

      
Application Number 17094984
Status Pending
Filing Date 2020-11-11
First Publication Date 2021-07-29
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Yan, Ke P.
  • Zhu, Zhuotun
  • Jin, Dakai
  • Cai, Jinzheng
  • Harrison, Adam P.
  • Guo, Dazhou
  • Lu, Le

Abstract

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.

IPC Classes  ?

  • G06T 7/00 - Image analysis
  • G06T 7/70 - Determining position or orientation of objects or cameras
  • G06T 11/00 - 2D [Two Dimensional] image generation
  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06K 9/46 - Extraction of features or characteristics of the image
  • G06T 9/00 - Image coding
  • A61B 6/03 - Computerised tomographs
  • A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
  • G06N 3/08 - Learning methods
  • G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
  • G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

35.

Data noise reduction method, device, computer apparatus and storage medium

      
Application Number 16634438
Grant Number 11321287
Status In Force
Filing Date 2018-12-24
First Publication Date 2021-07-29
Grant Date 2022-05-03
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Yu, Xiuming
  • Wang, Wei
  • Xiao, Jing

Abstract

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.

IPC Classes  ?

  • G06F 16/00 - Information retrieval; Database structures therefor; File system structures therefor
  • G06F 16/215 - Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
  • G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
  • G06F 16/23 - Updating
  • G06F 16/22 - Indexing; Data structures therefor; Storage structures
  • G06F 11/34 - Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation

36.

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

      
Application Number 16093628
Status Pending
Filing Date 2018-02-27
First Publication Date 2021-07-22
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor Wan, Xiaohui

Abstract

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.

IPC Classes  ?

  • G06F 30/20 - Design optimisation, verification or simulation
  • G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
  • G06Q 10/06 - Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models

37.

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

      
Application Number 16097992
Status Pending
Filing Date 2018-02-26
First Publication Date 2021-07-22
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Zhang, Jie
  • Gao, Xue
  • Li, Bin
  • Chen, Jie
  • Shao, Zhengbo
  • Ma, Xiangdong
  • Ding, Jie

Abstract

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.

IPC Classes  ?

  • G06Q 10/10 - Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
  • G06F 16/245 - Query processing
  • G06F 16/248 - Presentation of query results
  • G06Q 40/08 - Insurance, e.g. risk analysis or pensions
  • G06Q 30/00 - Commerce, e.g. shopping or e-commerce

38.

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

      
Application Number 16099425
Status Pending
Filing Date 2018-01-31
First Publication Date 2021-07-22
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Li, Fang
  • Wang, Jianming
  • Xiao, Jing

Abstract

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.

IPC Classes  ?

  • G06Q 30/02 - Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
  • G06Q 10/06 - Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
  • G06N 20/20 - Ensemble learning
  • G06N 5/00 - Computer systems using knowledge-based models
  • G06N 5/04 - Inference methods or devices
  • G06F 40/30 - Semantic analysis
  • H04M 3/523 - Centralised call answering arrangements requiring operator intervention with call distribution or queuing

39.

User permission data query method and apparatus, electronic device and medium

      
Application Number 16099672
Grant Number 11281793
Status In Force
Filing Date 2017-09-29
First Publication Date 2021-07-22
Grant Date 2022-03-22
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Dong, Chao
  • Chen, Yaozhang
  • Song, Junfei
  • He, Yongjia

Abstract

A user permission data query method which includes 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; 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 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.

IPC Classes  ?

  • G06F 7/04 - Identity comparison, i.e. for like or unlike values
  • H04N 7/16 - Analogue secrecy systems; Analogue subscription systems
  • G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
  • G06F 16/2455 - Query execution
  • G06F 16/22 - Indexing; Data structures therefor; Storage structures
  • G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
  • G06F 16/248 - Presentation of query results
  • G06F 21/60 - Protecting data

40.

METHOD AND SYSTEM FOR HARVESTING LESION ANNOTATIONS

      
Application Number 16984727
Status Pending
Filing Date 2020-08-04
First Publication Date 2021-07-22
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Cai, Jinzheng
  • Harrison, Adam P.
  • Yan, Ke
  • Huo, Yuankai
  • Lu, Le

Abstract

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.

IPC Classes  ?

  • G06T 7/00 - Image analysis
  • G06T 5/50 - Image enhancement or restoration by the use of more than one image, e.g. averaging, subtraction
  • G06T 19/20 - Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts

41.

Method and device for stratified image segmentation

      
Application Number 16928521
Grant Number 11315254
Status In Force
Filing Date 2020-07-14
First Publication Date 2021-07-22
Grant Date 2022-04-26
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Guo, Dazhou
  • Jin, Dakai
  • Zhu, Zhuotun
  • Harrison, Adam P
  • Lu, Le

Abstract

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.

IPC Classes  ?

42.

Topic monitoring for early warning with extended keyword similarity

      
Application Number 16090351
Grant Number 11205046
Status In Force
Filing Date 2017-06-28
First Publication Date 2021-07-22
Grant Date 2021-12-21
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Wang, Jianzong
  • Huang, Zhangcheng
  • Wu, Tianbo
  • Xiao, Jing

Abstract

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.

IPC Classes  ?

43.

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

      
Application Number 16097291
Grant Number 11164027
Status In Force
Filing Date 2017-08-31
First Publication Date 2021-07-22
Grant Date 2021-11-02
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Wang, Jianzong
  • Ma, Jin
  • Huang, Zhangcheng
  • Wu, Tianbo
  • Xiao, Jing

Abstract

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.

IPC Classes  ?

  • G06K 9/32 - Aligning or centering of the image pick-up or image-field
  • G06K 9/46 - Extraction of features or characteristics of the image
  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06N 3/08 - Learning methods

44.

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

      
Application Number 16097693
Grant Number 11190536
Status In Force
Filing Date 2017-10-30
First Publication Date 2021-07-22
Grant Date 2021-11-30
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor He, Shuangning

Abstract

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.

IPC Classes  ?

  • H04L 29/00 - Arrangements, apparatus, circuits or systems, not covered by a single one of groups
  • H04L 29/06 - Communication control; Communication processing characterised by a protocol

45.

DEVICE AND METHOD FOR UNIVERSAL LESION DETECTION IN MEDICAL IMAGES

      
Application Number 16983373
Status Pending
Filing Date 2020-08-03
First Publication Date 2021-07-22
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Yan, Ke
  • Cai, Jinzheng
  • Harrison, Adam P.
  • Jin, Dakai
  • Lu, Le

Abstract

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.

IPC Classes  ?

  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06T 7/00 - Image analysis
  • G06K 9/32 - Aligning or centering of the image pick-up or image-field
  • G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
  • G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
  • G06N 3/08 - Learning methods
  • G06N 3/04 - Architecture, e.g. interconnection topology

46.

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

      
Application Number 17142187
Status Pending
Filing Date 2021-01-05
First Publication Date 2021-07-15
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Zheng, Kang
  • Wang, Yirui
  • Miao, Shun
  • Kuo, Changfu
  • Hsieh, Chen-I

Abstract

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.

IPC Classes  ?

  • A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
  • G06T 7/11 - Region-based segmentation
  • G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
  • G06T 7/00 - Image analysis
  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06K 9/46 - Extraction of features or characteristics of the image
  • G06N 3/08 - Learning methods
  • G06N 3/04 - Architecture, e.g. interconnection topology
  • G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
  • G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment

47.

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

      
Application Number 16635554
Status Pending
Filing Date 2019-05-31
First Publication Date 2021-07-15
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Jin, Ge
  • Xu, Liang
  • Xiao, Jing

Abstract

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.

IPC Classes  ?

  • G06N 5/02 - Knowledge representation
  • G06N 3/08 - Learning methods
  • G06N 20/10 - Machine learning using kernel methods, e.g. support vector machines [SVM]
  • G06K 9/62 - Methods or arrangements for recognition using electronic means

48.

DEVICE AND METHOD FOR COMPUTER-AIDED DIAGNOSIS BASED ON IMAGE

      
Application Number 16850622
Status Pending
Filing Date 2020-04-16
First Publication Date 2021-07-15
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Wang, Yirui
  • Chen, Haomin
  • Zheng, Kang
  • Harrison, Adam
  • Lu, Le
  • Miao, Shun

Abstract

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.

IPC Classes  ?

  • A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
  • G06K 9/32 - Aligning or centering of the image pick-up or image-field
  • G06T 9/00 - Image coding
  • G06T 7/00 - Image analysis

49.

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

      
Application Number 17207144
Status Pending
Filing Date 2021-03-19
First Publication Date 2021-07-08
Owner PING AN TECHNOLOGY(SHENZHEN)CO., LTD. (China)
Inventor
  • Guo, Bingxue
  • Wang, Jiaping
  • Xie, Weiwei

Abstract

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.

IPC Classes  ?

  • G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
  • G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
  • G06T 7/11 - Region-based segmentation
  • G06K 9/03 - Detection or correction of errors, e.g. by rescanning the pattern
  • G06T 11/00 - 2D [Two Dimensional] image generation

50.

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

      
Application Number 16759368
Status Pending
Filing Date 2019-05-29
First Publication Date 2021-07-08
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Liu, Yuchao
  • Guo, Dian
  • Han, Ling

Abstract

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.

IPC Classes  ?

51.

Cultivated land recognition method in satellite image and computing device

      
Application Number 16727753
Grant Number 11157737
Status In Force
Filing Date 2019-12-26
First Publication Date 2021-07-01
Grant Date 2021-10-26
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Zhao, Yi
  • Qiao, Nan
  • Lin, Ruei-Sung
  • Gong, Bo
  • Han, Mei

Abstract

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.

IPC Classes  ?

  • G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
  • G06T 7/13 - Edge detection
  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06F 17/18 - Complex mathematical operations for evaluating statistical data

52.

Face swap method and computing device

      
Application Number 16729165
Grant Number 11120595
Status In Force
Filing Date 2019-12-27
First Publication Date 2021-07-01
Grant Date 2021-09-14
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Miao, Jinghong
  • Gou, Yuchuan
  • Li, Minghao
  • Lai, Jui-Hsin
  • Gong, Bo
  • Han, Mei

Abstract

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.

IPC Classes  ?

  • G06T 11/60 - Editing figures and text; Combining figures or text
  • G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
  • G06K 9/34 - Segmentation of touching or overlapping patterns in the image field

53.

INTELLIGENT MOBILITY ASSISTANCE DEVICE

      
Application Number 16729184
Status Pending
Filing Date 2019-12-27
First Publication Date 2021-07-01
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Qin, Chaoping
  • Xia, Tian
  • Han, Mei
  • Chang, Peng
  • Gong, Bo

Abstract

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.

IPC Classes  ?

  • A61G 7/10 - Devices for lifting patients or disabled persons, e.g. special adaptations of hoists thereto

54.

Environment monitoring method and electronic device

      
Application Number 16727763
Grant Number 11176371
Status In Force
Filing Date 2019-12-26
First Publication Date 2021-07-01
Grant Date 2021-11-16
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Yao, Xi
  • Chen, Qi
  • Lin, Ruei-Sung
  • Gong, Bo
  • Zhao, Yi
  • Han, Mei
  • Miao, Jinghong

Abstract

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.

IPC Classes  ?

  • G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
  • G06K 9/46 - Extraction of features or characteristics of the image
  • G06K 9/62 - Methods or arrangements for recognition using electronic means

55.

Image processing method and electronic device

      
Application Number 16727791
Grant Number 11080834
Status In Force
Filing Date 2019-12-26
First Publication Date 2021-07-01
Grant Date 2021-08-03
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Miao, Jinghong
  • Gou, Yuchuan
  • Gong, Bo
  • Han, Mei

Abstract

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.

IPC Classes  ?

  • G06T 5/50 - Image enhancement or restoration by the use of more than one image, e.g. averaging, subtraction
  • G06F 17/16 - Matrix or vector computation
  • G06N 3/04 - Architecture, e.g. interconnection topology

56.

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

      
Application Number 16729117
Grant Number 11062504
Status In Force
Filing Date 2019-12-27
First Publication Date 2021-07-01
Grant Date 2021-07-13
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Li, Minghao
  • Miao, Jinghong
  • Gou, Yuchuan
  • Gong, Bo
  • Han, Mei

Abstract

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.

IPC Classes  ?

  • G06T 15/20 - Perspective computation
  • G06T 5/00 - Image enhancement or restoration
  • G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints

57.

Crop identification method and computing device

      
Application Number 16727788
Grant Number 11328506
Status In Force
Filing Date 2019-12-26
First Publication Date 2021-07-01
Grant Date 2022-05-10
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Lin, Ruei-Sung
  • Qiao, Nan
  • Zhao, Yi
  • Gong, Bo
  • Han, Mei

Abstract

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.

IPC Classes  ?

  • G06T 5/00 - Image enhancement or restoration
  • G06T 5/20 - Image enhancement or restoration by the use of local operators
  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06V 20/10 - Terrestrial scenes

58.

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

      
Application Number 16726790
Grant Number 11120308
Status In Force
Filing Date 2019-12-24
First Publication Date 2021-06-24
Grant Date 2021-09-14
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Li, Kun
  • Zhang, Hao
  • Lin, Ruei-Sung
  • Han, Mei

Abstract

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.

IPC Classes  ?

  • G06K 9/62 - Methods or arrangements for recognition using electronic means

59.

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

      
Application Number 16093633
Status Pending
Filing Date 2017-10-31
First Publication Date 2021-06-24
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Jin, Xin
  • Wu, Zhuangwei
  • Zhang, Chuan
  • Zhao, Yuanyuan
  • Huang, Duxin
  • Liang, Yongjian
  • Huo, Li

Abstract

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.

IPC Classes  ?

  • B60W 40/09 - Driving style or behaviour
  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06N 3/08 - Learning methods

60.

Method for training image generation model and computer device

      
Application Number 16726785
Grant Number 11048971
Status In Force
Filing Date 2019-12-24
First Publication Date 2021-06-24
Grant Date 2021-06-29
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Miao, Jinghong
  • Gong, Bo
  • Han, Mei

Abstract

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.

IPC Classes  ?

  • G06K 9/62 - Methods or arrangements for recognition using electronic means

61.

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

      
Application Number 17167515
Status Pending
Filing Date 2021-02-04
First Publication Date 2021-06-17
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor Ye, Ming

Abstract

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.

IPC Classes  ?

  • G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
  • G06K 9/46 - Extraction of features or characteristics of the image
  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06T 3/40 - Scaling of a whole image or part thereof
  • G06N 3/08 - Learning methods

62.

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

      
Application Number 17178823
Status Pending
Filing Date 2021-02-18
First Publication Date 2021-06-10
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Chen, Minchuan
  • Ma, Jun
  • Wang, Shaojun

Abstract

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.

IPC Classes  ?

  • G10L 13/08 - Text analysis or generation of parameters for speech synthesis out of text, e.g. grapheme to phoneme translation, prosody generation or stress or intonation determination
  • G10L 25/24 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the type of extracted parameters the extracted parameters being the cepstrum
  • G10L 25/18 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the type of extracted parameters the extracted parameters being spectral information of each sub-band
  • G10L 13/047 - Architecture of speech synthesisers

63.

FINGER VEIN COMPARISON METHOD, COMPUTER EQUIPMENT, AND STORAGE MEDIUM

      
Application Number 17178911
Status Pending
Filing Date 2021-02-18
First Publication Date 2021-06-10
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Chao, Zhongdi
  • Zhuang, Bojin
  • Wang, Shaojun

Abstract

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).

IPC Classes  ?

  • G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
  • G06K 9/62 - Methods or arrangements for recognition using electronic means

64.

Scoring information matching method and device, storage medium and server

      
Application Number 16076583
Grant Number 11113706
Status In Force
Filing Date 2017-06-26
First Publication Date 2021-06-10
Grant Date 2021-09-07
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Chen, Bin
  • Zhang, Xinyu
  • Wang, Wei
  • Li, Pingmei

Abstract

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.

IPC Classes  ?

  • G06Q 30/02 - Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
  • G06Q 30/00 - Commerce, e.g. shopping or e-commerce
  • H04M 3/51 - Centralised call answering arrangements requiring operator intervention
  • H04M 3/42 - Systems providing special services or facilities to subscribers

65.

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

      
Application Number 16637274
Status Pending
Filing Date 2019-06-26
First Publication Date 2021-06-03
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Jin, Ge
  • Xu, Liang
  • Xiao, Jing

Abstract

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.

IPC Classes  ?

  • G06F 40/40 - Processing or translation of natural language
  • G06N 3/04 - Architecture, e.g. interconnection topology
  • G06N 3/08 - Learning methods

66.

IMAGE GENERATION METHOD AND COMPUTING DEVICE

      
Application Number 16701484
Status Pending
Filing Date 2019-12-03
First Publication Date 2021-06-03
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Miao, Jinghong
  • Gou, Yuchuan
  • Lin, Ruei-Sung
  • Gong, Bo
  • Han, Mei

Abstract

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.

IPC Classes  ?

  • G06K 9/48 - Extraction of features or characteristics of the image by coding the contour of the pattern
  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06K 9/46 - Extraction of features or characteristics of the image
  • G06T 7/13 - Edge detection
  • G06T 3/40 - Scaling of a whole image or part thereof
  • G06K 9/42 - Normalisation of the pattern dimensions
  • G06F 16/538 - Presentation of query results
  • G06F 16/56 - Information retrieval; Database structures therefor; File system structures therefor of still image data having vectorial format
  • G06N 3/04 - Architecture, e.g. interconnection topology
  • G06N 3/08 - Learning methods

67.

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

      
Application Number 17168884
Status Pending
Filing Date 2021-02-05
First Publication Date 2021-06-03
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Wang, Yue
  • Lv, Bin
  • Lv, Chuanfeng

Abstract

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.

IPC Classes  ?

  • G06T 7/00 - Image analysis
  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06K 9/46 - Extraction of features or characteristics of the image
  • G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
  • G06T 7/11 - Region-based segmentation
  • G06T 7/136 - Segmentation; Edge detection involving thresholding
  • G06T 7/187 - Segmentation; Edge detection involving connected component labelling
  • A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
  • A61B 6/03 - Computerised tomographs

68.

IMAGE GENERATION METHOD AND COMPUTING DEVICE

      
Application Number 16701474
Status Pending
Filing Date 2019-12-03
First Publication Date 2021-06-03
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Gou, Yuchuan
  • Miao, Jinghong
  • Lin, Ruei-Sung
  • Gong, Bo
  • Han, Mei

Abstract

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.

IPC Classes  ?

  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06T 3/40 - Scaling of a whole image or part thereof
  • G06N 3/08 - Learning methods
  • G06N 3/04 - Architecture, e.g. interconnection topology

69.

UNBALANCED SAMPLE DATA PREPROCESSING METHOD AND DEVICE, AND COMPUTER DEVICE

      
Application Number 17165640
Status Pending
Filing Date 2021-02-02
First Publication Date 2021-05-27
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Yu, Xiuming
  • Wang, Wei
  • Xiao, Jing

Abstract

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.

IPC Classes  ?

  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06F 7/24 - Sorting, i.e. extracting data from one or more carriers, re-arranging the data in numerical or other ordered sequence, and re-recording the sorted data on the original carrier or on a different carrier or set of carriers

70.

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

      
Application Number 17167466
Status Pending
Filing Date 2021-02-04
First Publication Date 2021-05-27
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor Chen, Lin

Abstract

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.

IPC Classes  ?

  • G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
  • G10L 17/22 - Interactive procedures; Man-machine interfaces

71.

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

      
Application Number 17168925
Status Pending
Filing Date 2021-02-05
First Publication Date 2021-05-27
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Chen, Xianxian
  • Ruan, Xiaowen
  • Xu, Liang

Abstract

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).

IPC Classes  ?

  • G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
  • G06N 20/20 - Ensemble learning

72.

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

      
Application Number 16095803
Grant Number 11122128
Status In Force
Filing Date 2018-01-23
First Publication Date 2021-04-29
Grant Date 2021-09-14
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor Yan, Baohang

Abstract

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.

IPC Classes  ?

  • G06F 15/16 - Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
  • H04L 29/08 - Transmission control procedure, e.g. data link level control procedure
  • G06F 40/174 - Form filling; Merging

73.

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

      
Application Number 16097850
Grant Number 11030998
Status In Force
Filing Date 2017-08-31
First Publication Date 2021-04-29
Grant Date 2021-06-08
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Liang, Hao
  • Wang, Jianzong
  • Cheng, Ning
  • Xiao, Jing

Abstract

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.

IPC Classes  ?

  • G10L 15/14 - Speech classification or search using statistical models, e.g. Hidden Markov Models [HMM]
  • G10L 15/02 - Feature extraction for speech recognition; Selection of recognition unit
  • G10L 15/16 - Speech classification or search using artificial neural networks

74.

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

      
Application Number 16084980
Grant Number 11061925
Status In Force
Filing Date 2017-08-31
First Publication Date 2021-04-29
Grant Date 2021-07-13
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor Fu, Jun

Abstract

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.

IPC Classes  ?

  • G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
  • G06F 16/21 - Design, administration or maintenance of databases
  • G06F 9/48 - Program initiating; Program switching, e.g. by interrupt

75.

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

      
Application Number 16090198
Grant Number 11074443
Status In Force
Filing Date 2017-08-30
First Publication Date 2021-04-29
Grant Date 2021-07-27
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Wang, Jianzong
  • Wang, Chenyu
  • Ma, Jin
  • Xiao, Jing

Abstract

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.

IPC Classes  ?

  • G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
  • G06T 7/12 - Edge-based segmentation
  • G06K 9/38 - Quantising the analogue image signal
  • G06K 9/46 - Extraction of features or characteristics of the image
  • G06T 7/60 - Analysis of geometric attributes
  • G06T 7/11 - Region-based segmentation
  • G06K 9/32 - Aligning or centering of the image pick-up or image-field

76.

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

      
Application Number 16729154
Grant Number 10991154
Status In Force
Filing Date 2019-12-27
First Publication Date 2021-04-27
Grant Date 2021-04-27
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Li, Minghao
  • Miao, Jinghong
  • Gou, Yuchuan
  • Gong, Bo
  • Han, Mei

Abstract

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.

IPC Classes  ?

  • G06T 17/00 - 3D modelling for computer graphics
  • G06T 19/20 - Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
  • G06N 3/08 - Learning methods
  • G06N 3/04 - Architecture, e.g. interconnection topology

77.

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

      
Application Number 16084242
Status Pending
Filing Date 2017-08-31
First Publication Date 2021-04-22
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor Chen, Yiyun

Abstract

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.

IPC Classes  ?

  • G06Q 30/02 - Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
  • G06F 30/10 - Geometric CAD
  • G06N 20/00 - Machine learning

78.

Enhanced medical images processing method and computing device

      
Application Number 16710086
Grant Number 10984530
Status In Force
Filing Date 2019-12-11
First Publication Date 2021-04-20
Grant Date 2021-04-20
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Yao, Jiawen
  • Jin, Dakai
  • Lu, Le

Abstract

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.

IPC Classes  ?

  • G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
  • G06T 7/00 - Image analysis
  • G06T 7/136 - Segmentation; Edge detection involving thresholding
  • G06T 7/38 - Registration of image sequences

79.

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

      
Application Number 16634010
Status Pending
Filing Date 2018-02-23
First Publication Date 2021-04-01
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD (China)
Inventor Zhang, Shuzi

Abstract

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.

IPC Classes  ?

  • G06F 16/951 - Indexing; Web crawling techniques
  • H04L 29/12 - Arrangements, apparatus, circuits or systems, not covered by a single one of groups characterised by the data terminal
  • G06F 16/953 - Querying, e.g. by the use of web search engines
  • H04L 29/06 - Communication control; Communication processing characterised by a protocol

80.

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

      
Application Number 16084233
Grant Number 11068571
Status In Force
Filing Date 2017-08-31
First Publication Date 2021-04-01
Grant Date 2021-07-20
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Wang, Jianzong
  • Guo, Hui
  • Xiao, Jing

Abstract

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.

IPC Classes  ?

  • G06F 21/32 - User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
  • G06N 3/04 - Architecture, e.g. interconnection topology
  • G10L 17/18 - Artificial neural networks; Connectionist approaches
  • G10L 17/22 - Interactive procedures; Man-machine interfaces
  • G10L 25/24 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the type of extracted parameters the extracted parameters being the cepstrum

81.

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

      
Application Number 16088831
Grant Number 11010227
Status In Force
Filing Date 2017-09-30
First Publication Date 2021-04-01
Grant Date 2021-05-18
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Du, Yuan
  • Ye, Longfei

Abstract

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.

IPC Classes  ?

  • G06F 11/00 - Error detection; Error correction; Monitoring
  • G06F 11/07 - Responding to the occurrence of a fault, e.g. fault tolerance
  • G06F 11/34 - Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation
  • G06F 11/30 - Monitoring

82.

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

      
Application Number 16084993
Status Pending
Filing Date 2017-09-30
First Publication Date 2021-03-25
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Wang, Jianzong
  • Wang, Chenyu
  • Ma, Jin
  • Xiao, Jing

Abstract

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.

IPC Classes  ?

  • G06Q 40/08 - Insurance, e.g. risk analysis or pensions
  • G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
  • G06K 9/62 - Methods or arrangements for recognition using electronic means

83.

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

      
Application Number 16084231
Grant Number 11059174
Status In Force
Filing Date 2017-06-30
First Publication Date 2021-03-18
Grant Date 2021-07-13
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Zhou, Taotao
  • Zhou, Bao
  • Xiao, Jing

Abstract

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.

IPC Classes  ?

  • G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions
  • B25J 9/16 - Programme controls
  • G05D 1/02 - Control of position or course in two dimensions
  • G06T 17/00 - 3D modelling for computer graphics

84.

Path planning system and method for robot, robot and medium

      
Application Number 16084245
Grant Number 11035684
Status In Force
Filing Date 2017-06-30
First Publication Date 2021-03-18
Grant Date 2021-06-15
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Zhou, Chen
  • Zhou, Bao
  • Xiao, Jing

Abstract

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.

IPC Classes  ?

  • G01C 21/34 - Route searching; Route guidance
  • G05D 1/00 - Control of position, course, altitude, or attitude of land, water, air, or space vehicles, e.g. automatic pilot
  • G05D 1/02 - Control of position or course in two dimensions

85.

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

      
Application Number 16084232
Status Pending
Filing Date 2017-06-30
First Publication Date 2021-03-18
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Jin, Ge
  • Xu, Liang
  • Xiao, Jing

Abstract

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.

IPC Classes  ?

  • G06N 20/20 - Ensemble learning
  • G06N 5/00 - Computer systems using knowledge-based models
  • G06Q 10/10 - Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting

86.

Speech recognition method, apparatus, and computer readable storage medium

      
Application Number 16642371
Grant Number 11081103
Status In Force
Filing Date 2017-11-28
First Publication Date 2021-03-11
Grant Date 2021-08-03
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Liang, Hao
  • Cheng, Ning
  • Wang, Jianzong
  • Xiao, Jing

Abstract

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.

IPC Classes  ?

  • G10L 15/22 - Procedures used during a speech recognition process, e.g. man-machine dialog
  • G10L 15/06 - Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
  • G10L 15/02 - Feature extraction for speech recognition; Selection of recognition unit
  • G10L 15/16 - Speech classification or search using artificial neural networks
  • G10L 15/18 - Speech classification or search using natural language modelling

87.

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

      
Application Number 16960031
Status Pending
Filing Date 2018-05-28
First Publication Date 2021-03-04
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor Zhou, Shenglong

Abstract

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.

IPC Classes  ?

  • H04L 29/06 - Communication control; Communication processing characterised by a protocol
  • G06F 16/903 - Querying
  • G06F 40/289 - Phrasal analysis, e.g. finite state techniques or chunking
  • H04L 29/08 - Transmission control procedure, e.g. data link level control procedure

88.

METHOD AND DEVICE FOR GENERATING MEDICAL REPORT

      
Application Number 16633707
Status Pending
Filing Date 2018-07-19
First Publication Date 2021-02-25
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Wang, Chenyu
  • Wang, Jianzong
  • Xiao, Jing

Abstract

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.

IPC Classes  ?

  • G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
  • G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
  • G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
  • G06N 3/04 - Architecture, e.g. interconnection topology

89.

Medical image classification method and related device

      
Application Number 16546627
Grant Number 10997720
Status In Force
Filing Date 2019-08-21
First Publication Date 2021-02-25
Grant Date 2021-05-04
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Zhou, Bo
  • Harrison, Adam Patrick
  • Yao, Jiawen
  • Lu, Le

Abstract

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.

IPC Classes  ?

  • G06T 7/00 - Image analysis
  • G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
  • G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
  • G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06T 7/11 - Region-based segmentation
  • G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

90.

Clinical target volume delineation method and electronic device

      
Application Number 16546615
Grant Number 11040219
Status In Force
Filing Date 2019-08-21
First Publication Date 2021-02-25
Grant Date 2021-06-22
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Jin, Dakai
  • Guo, Dazhou
  • Lu, Le
  • Harrison, Adam Patrick

Abstract

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.

IPC Classes  ?

  • A61N 5/10 - X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy
  • G06T 7/00 - Image analysis
  • G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
  • G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
  • A61B 6/03 - Computerised tomographs

91.

Fracture detection method, electronic device and storage medium

      
Application Number 16546624
Grant Number 10937143
Status In Force
Filing Date 2019-08-21
First Publication Date 2021-02-25
Grant Date 2021-03-02
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Wang, Yirui
  • Lu, Le
  • Jin, Dakai
  • Harrison, Adam Patrick
  • Miao, Shun

Abstract

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.

IPC Classes  ?

92.

Gross tumor volume segmentation method and computer device

      
Application Number 16546604
Grant Number 10929981
Status In Force
Filing Date 2019-08-21
First Publication Date 2021-02-23
Grant Date 2021-02-23
Owner Ping An Technology (Shenzhen) Co., Ltd. (China)
Inventor
  • Jin, Dakai
  • Guo, Dazhou
  • Lu, Le
  • Harrison, Adam Patrick

Abstract

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.

IPC Classes  ?

  • G06T 7/174 - Segmentation; Edge detection involving the use of two or more images
  • G06T 7/30 - Determination of transform parameters for the alignment of images, i.e. image registration
  • G06T 7/11 - Region-based segmentation

93.

Methods and devices for optimizing load balancing based on cloud monitoring

      
Application Number 16075327
Grant Number 10992581
Status In Force
Filing Date 2017-10-24
First Publication Date 2021-02-04
Grant Date 2021-04-27
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Kuang, Guangcai
  • Yi, Renjie

Abstract

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.

IPC Classes  ?

  • H04L 12/26 - Monitoring arrangements; Testing arrangements
  • H04L 12/803 - Load balancing, e.g. traffic distribution over multiple links
  • H04L 29/08 - Transmission control procedure, e.g. data link level control procedure

94.

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

      
Application Number 16318818
Grant Number 10977447
Status In Force
Filing Date 2017-09-28
First Publication Date 2021-02-04
Grant Date 2021-04-13
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Wang, Jianzong
  • Huang, Zhangcheng
  • Wu, Tianbo
  • Xiao, Jing

Abstract

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.

IPC Classes  ?

95.

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

      
Application Number 16098129
Grant Number 11093631
Status In Force
Filing Date 2018-02-28
First Publication Date 2020-11-12
Grant Date 2021-08-17
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Tan, Zhijie
  • Liang, Yongjian
  • Zhang, Chuan

Abstract

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.

IPC Classes  ?

  • G08B 23/00 - Alarms responsive to unspecified undesired or abnormal conditions
  • G06F 12/16 - Protection against loss of memory contents
  • G06F 12/14 - Protection against unauthorised use of memory
  • G06F 11/00 - Error detection; Error correction; Monitoring
  • G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
  • G06F 16/2457 - Query processing with adaptation to user needs
  • G06F 16/22 - Indexing; Data structures therefor; Storage structures
  • G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
  • G06F 21/31 - User authentication

96.

Data transmission method, apparatus, terminal device, and medium

      
Application Number 16088807
Grant Number 11146571
Status In Force
Filing Date 2018-02-26
First Publication Date 2020-10-01
Grant Date 2021-10-12
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Tian, Zhengwei
  • Feng, Chao
  • Xue, Yan

Abstract

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.

IPC Classes  ?

  • H04L 29/06 - Communication control; Communication processing characterised by a protocol
  • G06F 16/901 - Indexing; Data structures therefor; Storage structures
  • G06Q 30/02 - Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination

97.

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

      
Application Number 16084565
Status Pending
Filing Date 2017-06-30
First Publication Date 2020-09-24
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Wang, Jianzong
  • Huang, Zhangcheng
  • Wu, Tianbo
  • Xiao, Jing

Abstract

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.

IPC Classes  ?

  • G06Q 10/04 - Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"
  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06N 20/00 - Machine learning
  • G06N 7/00 - Computer systems based on specific mathematical models

98.

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

      
Application Number 16088061
Grant Number 10887171
Status In Force
Filing Date 2018-02-13
First Publication Date 2020-09-24
Grant Date 2021-01-05
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor Jin, Mengjie

Abstract

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.

IPC Classes  ?

  • G06F 15/173 - Interprocessor communication using an interconnection network, e.g. matrix, shuffle, pyramid, star or snowflake
  • H04L 12/24 - Arrangements for maintenance or administration
  • H04L 29/08 - Transmission control procedure, e.g. data link level control procedure

99.

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

      
Application Number 16759383
Status Pending
Filing Date 2018-07-13
First Publication Date 2020-09-17
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Wang, Jianzong
  • Wang, Chenyu
  • Ma, Jin
  • Xiao, Jing

Abstract

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.

IPC Classes  ?

  • G06T 7/10 - Segmentation; Edge detection
  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06N 3/08 - Learning methods
  • G06N 3/06 - Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons

100.

Method and apparatus for establishing voiceprint model, computer device, and storage medium

      
Application Number 16759384
Grant Number 11322155
Status In Force
Filing Date 2018-07-06
First Publication Date 2020-09-17
Grant Date 2022-05-03
Owner PING AN TECHNOLOGY (SHENZHEN) CO., LTD. (China)
Inventor
  • Cai, Yuanzhe
  • Wang, Jianzong
  • Cheng, Ning
  • Xiao, Jing

Abstract

A method and apparatus for establishing a voiceprint model, a computer device, and a storage medium are described herein. The method includes: collecting speech acoustic features in a speech signal to form a plurality of cluster structures; calculating an average value and a standard deviation of the plurality of cluster structures and then performing coordinate transformation and activation function calculation to obtain a feature vector; and obtaining a voiceprint model based on the feature vector.

IPC Classes  ?

  • G10L 17/04 - Training, enrolment or model building
  • G06F 17/18 - Complex mathematical operations for evaluating statistical data
  • G06K 9/62 - Methods or arrangements for recognition using electronic means
  • G06N 3/04 - Architecture, e.g. interconnection topology
  • G06N 3/08 - Learning methods
  • G10L 15/02 - Feature extraction for speech recognition; Selection of recognition unit
  • G10L 15/16 - Speech classification or search using artificial neural networks
  • G10L 17/02 - Preprocessing operations, e.g. segment selection; Pattern representation or modelling, e.g. based on linear discriminant analysis [LDA] or principal components; Feature selection or extraction
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