Abrégé

Incidents may be monitored using a camera in response to an activation of a trigger device. Trigger data may be received over a communication network in response to activation of a trigger device disposed within a first area of a vehicle. A camera disposed within a second area of the vehicle may be controlled over the communication network in response to receiving the trigger data, the controlling causing the camera to capture sensor information of a passenger of the vehicle. Passenger information of the passenger of the vehicle may be obtained in response to receiving the trigger data. An alert notification may be generated. The alert notification may comprise at least a portion of the sensor information of the passenger, and the alert notification may be capable of initiating one or more incident actions associated with the passenger.

Classes IPC  ?

• G06V 20/59 - Contexte ou environnement de l’image à l’intérieur d’un véhicule, p.ex. concernant l’occupation des sièges, l’état du conducteur ou les conditions de l’éclairage intérieur
• H04W 4/48 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p.ex. communication véhicule-piétons pour la communication dans le véhicule
• B60R 25/30 - Détection relative au vol ou autres événements relatifs aux systèmes antivol
• B60R 25/102 - VÉHICULES, ÉQUIPEMENTS OU PARTIES DE VÉHICULES, NON PRÉVUS AILLEURS Équipements ou systèmes pour interdire ou signaler l’usage non autorisé ou le vol de véhicules actionnant un dispositif d’alarme un signal étant envoyé vers un lieu distant, p.ex. signal radio transmis à un poste de police, à une entreprise de sécurité ou au propriétaire du véhicule
• G06V 40/16 - Visages humains, p.ex. parties du visage, croquis ou expressions
• H04N 23/65 - Commande du fonctionnement de la caméra en fonction de l'alimentation électrique

Abrégé

Techniques for automatically detecting when a ride requester has requested a ride-share ride on behalf of a guest rider using some or all of the communications between the driver and ride requester are described herein. For example, a server can obtain chat logs between a ride requester and a driver and process the chat logs to identify whether the ride requester has requested a ride on behalf of a guest rider. In particular, the server can train an artificial intelligence model (e.g., a machine learning model) to predict potential guest rider behavior. Once trained, the server can obtain chat logs comprising chat messages sent between a driver and a ride requester, and apply a representation of the chat logs as an input to the trained artificial intelligence model to determine whether guest rider behavior is detected.

Classes IPC  ?

• G06Q 10/02 - Réservations, p.ex. pour billetterie, services ou manifestations
• G06Q 50/30 - Transport; Communications
• G10L 17/06 - Techniques de prise de décision; Stratégies d’alignement de motifs
• G06N 20/00 - Apprentissage automatique
• G06F 18/213 - Extraction de caractéristiques, p.ex. en transformant l'espace des caractéristiques; Synthétisations; Mappages, p.ex. procédés de sous-espace
• G06F 18/214 - Génération de motifs d'entraînement; Procédés de Bootstrapping, p.ex. ”bagging” ou ”boosting”

Abrégé

The present disclosure relates to systems and methods for displaying one or more points of interest (POIs) of a location-based service (LBS). The method may include receiving a request for an LBS sent by a user via a user terminal and obtaining a start location based on the request for the LBS. The method may also include determining one or more recommended POIs based on the start location and POI data associated with the start location. Further, the method may also include transmitting signals to the user terminal to display at least one of the one or more recommended POIs.

Classes IPC  ?

• G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire
• G01C 21/36 - Dispositions d'entrée/sortie pour des calculateurs embarqués

Abrégé

The present disclosure relates to systems and methods for displaying vehicle information for an on-demand service. The method may include sending a request for on-demand service to a server. The method may further include obtaining information of a vehicle related to the request for on-demand service. The information of the vehicle may include color information of the vehicle. The method may further include generating, by a processor, a user interface based on the information of the vehicle. The user interface may include at least one user interface element corresponding to the color information of the vehicle.

Classes IPC  ?

• G06T 11/00 - Génération d'images bidimensionnelles [2D]
• H04W 4/44 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p.ex. communication véhicule-piétons pour la communication entre véhicules et infrastructures, p.ex. véhicule à nuage ou véhicule à domicile
• G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire
• G06T 11/60 - Edition de figures et de texte; Combinaison de figures ou de texte
• H04L 67/51 - Découverte ou gestion de ceux-ci, p.ex. protocole de localisation de service [SLP] ou services du Web
• H04L 67/63 - Ordonnancement ou organisation du service des demandes d'application, p.ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises en acheminant une demande de service en fonction du contenu ou du contexte de la demande

Abrégé

The present disclosure provides a pick-up point recommendation method and system, an electronic device, a medium, and a program product. The pick-up point recommendation method comprises: acquiring travel information of a user, the travel information comprising initial travel starting point information and travel destination information; when the user enables a recommendation function, on the basis of the travel information, determining a recommended pick-up point from among a plurality of candidate pick-up points corresponding to the initial travel starting point information, the distance of a route between the recommended pick-up point and a travel destination of the user satisfying a preset condition; and displaying on a travel information display page position information of the recommended pick-up point, the position information of the recommended pick-up point being used to update the initial travel starting point information in the travel information.

Classes IPC  ?

• G06F 16/9537 - Recherche à dépendance spatiale ou temporelle, p.ex. requêtes spatio-temporelles

Abrégé

Embodiments of the present invention provide a meeting assistance method and system, and a storage medium. The method comprises: determining the distance between a service provider and a preset meeting position; when the distance is smaller than a distance threshold, instructing the service provider or a vehicle corresponding to the service provider to send a short-range wireless communication signal; instructing a service requester to establish a communication connection to the service provider or the vehicle on the basis of the short-range wireless communication signal; and guiding, on the basis of the communication connection, the service requester to meet the service provider.

Classes IPC  ?

• H04W 4/02 - Services utilisant des informations de localisation

Abrégé

Embodiments of the present application provide a method and apparatus for managing combined travel. The method provided herein comprises: acquiring trip information, wherein the trip information at least indicates a start point and an end point of a trip; and presenting combined travel recommendation information on a shared travel service interface, wherein the combined travel recommendation information is used for describing a target combined travel route, the target combined travel route is determined on the basis of the trip information, and the shared travel service interface further provides at least one candidate shared travel service for the trip. On the basis of such a mode, the embodiments of the present application can provide recommendation information for a combined travel route on the shared travel service interface, so as to provide richer travel choices for a user.

Classes IPC  ?

• G06F 16/9537 - Recherche à dépendance spatiale ou temporelle, p.ex. requêtes spatio-temporelles

Abrégé

The present disclosure provides a carpooling method and system, an electronic device, a medium, and a program product. The method comprises: obtaining and displaying, on the basis of departure point information of a first client, description information of at least one available vehicle; in response to receiving a trigger operation for the description information of any available vehicle, displaying travel detail information corresponding to the any available vehicle, information about each station in a travel route of the any available vehicle being displayed in the travel detail information; and generating carpooling order information according to the selected destination station information in the information about each station of the any available vehicle, and sending the carpooling order information to a server.

Classes IPC  ?

• G06Q 50/30 - Transport; Communications

Abrégé

The embodiments of the present disclosure provide a method, an apparatus, a storage medium, and an electronic device for information exchange. After receiving task information of a task, a task processing terminal may send its own position. A task issuing terminal may control a display device to render and display a position modification control corresponding to the task. In response to the position modification control is triggered, the task issuing terminal may display a modification page to detect a input operation. In response to that the input operation is detected, the task issuing terminal may determine corresponding position information and send position modification information determined based on the position information to a server. The server may obtain the task information and send, in response to that a task processing state of the task is unprocessed, a position modification prompt and the position modification information, so that the task processing terminal may modify a starting position of the task based on the position information. The method in the embodiments of the present disclosure may reduce a possibility of a task being cancelled and improve a utilization rate of task processing resources.

Classes IPC  ?

• G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire
• G01C 21/00 - Navigation; Instruments de navigation non prévus dans les groupes
• G06Q 50/30 - Transport; Communications

Abrégé

The present disclosure relates to a method and system for monitoring on route transportations. The method includes obtaining a driving route of a target vehicle; obtaining a reference position on the driving route away from a first current position of the target vehicle; determining a second current position of the target vehicle after a reference time; determining a distance between the second current position and the reference position is greater than a preset distance; and sending a signal to a target terminal indicating that the target vehicle is off-route.

Classes IPC  ?

• G08B 25/01 - Systèmes d'alarme dans lesquels l'emplacement du lieu où existe la condition déclenchant l'alarme est signalé à une station centrale, p.ex. systèmes télégraphiques d'incendie ou de police caractérisés par le moyen de transmission
• H04W 4/029 - Services de gestion ou de suivi basés sur la localisation
• G08G 1/005 - Systèmes de commande du trafic pour véhicules routiers comprenant un indicateur pour guider les piétons
• G08G 1/0968 - Systèmes impliquant la transmission d'indications de navigation au véhicule
• G08G 1/0969 - Systèmes impliquant la transmission d'indications de navigation au véhicule ayant un dispositif de visualisation sous forme de carte
• G08G 1/00 - Systèmes de commande du trafic pour véhicules routiers
• H04W 4/90 - Services pour gérer les situations d’urgence ou dangereuses, p.ex. systèmes d’alerte aux séismes et aux tsunamis
• G08B 25/08 - Systèmes d'alarme dans lesquels l'emplacement du lieu où existe la condition déclenchant l'alarme est signalé à une station centrale, p.ex. systèmes télégraphiques d'incendie ou de police caractérisés par le moyen de transmission utilisant les lignes de communication
• H04W 4/024 - Services d’orientation
• H04W 4/44 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p.ex. communication véhicule-piétons pour la communication entre véhicules et infrastructures, p.ex. véhicule à nuage ou véhicule à domicile
• G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p.ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
• G06F 3/00 - Dispositions d'entrée pour le transfert de données destinées à être traitées sous une forme maniable par le calculateur; Dispositions de sortie pour le transfert de données de l'unité de traitement à l'unité de sortie, p.ex. dispositions d'interface
• G06Q 50/26 - Services gouvernementaux ou services publics
• G08B 21/02 - Alarmes pour assurer la sécurité des personnes
• G08B 25/10 - Systèmes d'alarme dans lesquels l'emplacement du lieu où existe la condition déclenchant l'alarme est signalé à une station centrale, p.ex. systèmes télégraphiques d'incendie ou de police caractérisés par le moyen de transmission utilisant des systèmes de transmission sans fil

Abrégé

The present disclosure may provide an information interaction method, apparatus, electronic device, and readable storage medium relating to the field of computer technology. The method may include: in response to monitoring that an expected pick-up location is within a preset coordinate range, displaying at least one pick-up area within the preset coordinate range, wherein the expected pick-up location is a coordinate point of a map; receiving a pick-up area selecting instruction, and determining a target pick-up area; determining a target pick-up location corresponding to the target pick-up area; determining a recommended route between a current location and the target pick-up location in response to receiving a submitting instruction for the target pick-up location; based on the recommended route, displaying route guidance information.

Classes IPC  ?

• G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire
• G01C 21/36 - Dispositions d'entrée/sortie pour des calculateurs embarqués

Abrégé

Methods, systems, and apparatus, including computer programs encoded on computer storage media for acoustic echo cancellation and suppression are provided. An exemplary method comprises receiving a far-end acoustic signal and a corrupted near-end acoustic signal, wherein the corrupted near-end acoustic signal is generated based on (1) an echo of the far-end acoustic signal and (2) a near-end acoustic signal; feeding the far-end acoustic signal and the corrupted near-end acoustic signal into a neural network as an input to output a time-frequency (TF) mask that suppresses the echo and retains the near-end acoustic signal, and generating an enhanced version of the corrupted near-end acoustic signal by applying the obtained TF mask to the corrupted near-end acoustic signal.

Classes IPC  ?

• G06N 3/08 - Méthodes d'apprentissage
• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux

Abrégé

Methods, systems, and apparatus, including computer programs encoded on computer storage media for evaluating and improving live translation captioning systems. An exemplary method includes: displaying a word in a first language; receiving a first audio sequence, the first audio sequence comprising a verbal description of the word; generating a first translated text in a second language; displaying the first translated text; receiving a second audio sequence, the second audio sequence comprising a guessed word based on the first translated text; generating a second translated text in the first language; determining a matching score between the word and the second translated text; determining a performance score of the live translation captioning system based on the matching score.

Classes IPC  ?

• G06F 40/00 - Maniement de données en langage naturel
• G10L 15/32 - Reconnaisseurs multiples utilisés en séquence ou en parallèle; Systèmes de combinaison de score à cet effet, p.ex. systèmes de vote
• G10L 15/08 - Classement ou recherche de la parole
• G10L 15/06 - Création de gabarits de référence; Entraînement des systèmes de reconnaissance de la parole, p.ex. adaptation aux caractéristiques de la voix du locuteur
• G06F 40/49 - Traduction appuyée sur des données utilisant de très grands corpus, p.ex. le Web
• G06F 40/51 - Traitement ou traduction du langage naturel Évaluation de la traduction
• G06F 40/58 - Utilisation de traduction automatisée, p.ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel
• G10L 25/27 - Techniques d'analyses de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par la technique d’analyse

Abrégé

In accordance with one implementation of the present disclosure, a new approach for determining a movement orientation of a user is proposed in indoor navigation. Generally speaking, a device orientation of a terminal device is obtained based on at least one signal stream collected from the terminal device carried by a moving user. A deviation degree is determined based on the at least one signal stream, here the deviation degree represents a deviation between a movement orientation of the user and an actual device orientation of the terminal device. The movement orientation is determined based on the device orientation in accordance with a determination that the deviation degree is below a threshold degree. With the above implementation, the movement orientation of the user is determined in a more effective an accurate way, and thus accuracy of the indoor navigation is increased.

Classes IPC  ?

• G01C 21/20 - Instruments pour effectuer des calculs de navigation
• G01C 21/16 - Navigation; Instruments de navigation non prévus dans les groupes en utilisant des mesures de la vitesse ou de l'accélération exécutées à bord de l'objet navigant; Navigation à l'estime en intégrant l'accélération ou la vitesse, c. à d. navigation par inertie
• H04W 4/33 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les environnements intérieurs, p.ex. les bâtiments
• H04W 4/02 - Services utilisant des informations de localisation

Abrégé

The present disclosure provides a method, a first service requester, a system, and an electronic device for information display. The method may include obtaining a service request location where a first service requester is located when a carpooling request of the first service requester is received; determining dynamic carpooling information of at least one second service requester within a preset distance from the service request location during a carpooling process; and displaying the dynamic carpooling information of the at least one second service requester on a display interface of the first service request terminal. Therefore, the dynamic carpooling information of the at least one second service requester within the preset range from the service request location of the first service requester may be displayed to the first service requester during the time period waiting for the carpooling request of the first service requester to be responded, which can effectively enrich the display content of the service requester terminal, improve the transparency of the relevant information, fill the idle time that the user is waiting, and reduce the probability of the order cancellation.

Classes IPC  ?

• G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire
• G06Q 10/02 - Réservations, p.ex. pour billetterie, services ou manifestations

Abrégé

In accordance with one implementation of the present disclosure, a new approach for identifying a stepping event is proposed in indoor navigation. Generally speaking, a first signal fragment and a second signal fragment respectively within a first time window and a second time window in an acceleration signal stream are obtained, here the acceleration signal stream is collected from an acceleration sensor associated with a moving user, the first time window being shorter than the second time window. A first amplitude feature and a second amplitude feature are determined for the first and second time windows based on the first and second signal fragments, respectively. A stepping event of the user is identified based on a deviation between the first and second amplitude features. With the above implementation, the stepping event is identified in a more effective an accurate way, and thus accuracy of the indoor navigation is increased.

Classes IPC  ?

• G01C 22/00 - Mesure de la distance parcourue sur le sol par des véhicules, des personnes, des animaux ou autres corps solides en mouvement, p.ex. en utilisant des odomètres ou en utilisant des podomètres
• G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques

Abrégé

Systems and methods for online to offline services are provided. The methods may include obtaining a first service request issued by a first service requester, the first service request including a request time point, a start location, and a destination. The methods may further include determining a target time point based on at least one of the request time point or an input by the first service requester, wherein the target time point is after the request time point. The methods may further include obtaining one or more candidate service requests, and determining a service request set and a target service provider that matches with the service request set by executing, starting at the target time point, a matching process based on the first service request and the one or more candidate service requests. The service request set may include the first service request.

Classes IPC  ?

• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation

Abrégé

Provided in the present application are an information pushing method and apparatus, and an electronic device and a storage medium. The information pushing method comprises: receiving a selection operation which is for a message pushing icon and is issued by a first user in a first display interface of a first target program, and displaying a second display interface, wherein the first display interface and the second display interface are two interfaces which both belong to the first target program; receiving a selection operation of the first user for a second user in a message user list to be pushed that is in the second display interface, and acquiring second user identification information corresponding to the second user selected by the first user; and in a second target program, pushing a target message to the second user by means of a second target program user identifier corresponding to the second user identification information, wherein the second target program and the first target program are two different programs. By means of the present application, the efficiency of a first user pushing a message to other users can be improved.

Classes IPC  ?

• H04L 12/54 - Systèmes de commutation par mémorisation et restitution
• G06F 9/54 - Communication interprogramme

Abrégé

Embodiments of the disclosure provide systems and methods for verifying digital payments for a payment platform. The system includes a communication interface configured to receive service data associated with a transaction from a terminal device associated with a user of the payment platform. The system further includes at least one processor configured to automatically determine whether an authentication is waived for the transaction based on the received service data and a blacklist generated using a machine learning model. The blacklist includes a list of suspicious users and transaction behaviors. The at least one processor further configured to approve the transaction without requesting user authentication information from the terminal device when the authentication is waived. The at least one processor also configured to request the user authentication information from the terminal device and validate the user authentication information when the authentication is not waived.

Classes IPC  ?

• G06Q 30/00 - Commerce
• G06Q 10/10 - Bureautique; Gestion du temps
• G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
• G06Q 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p.ex. une autorité de certification, un notaire ou un tiers de confiance
• G06N 20/00 - Apprentissage automatique
• G06F 21/31 - Authentification de l’utilisateur
• G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil

Abrégé

After determining a trip order has a high risk, verification information unavailable in a passenger information database system can be requested and provided for a passenger of the account. Validity of the verification information can be determined using a verification service and stored in a passenger information database. A decision for the trip order can be determined based on the validity of the verification information stored in the passenger information database.

Classes IPC  ?

• G06Q 10/0631 - Planification, affectation, distribution ou ordonnancement de ressources d’entreprises ou d’organisations
• G06F 16/25 - Systèmes d’intégration ou d’interfaçage impliquant les systèmes de gestion de bases de données
• H04L 9/40 - Protocoles réseaux de sécurité
• G06Q 50/30 - Transport; Communications

Abrégé

The present disclosure relates to a system and a method for identifying a drunk passenger of a car hailing order. The system may perform the method to: obtain a plurality of samples from historical car hailing orders stored in a database; for each of the plurality of samples, using an application, extract a plurality of features including a passenger feature set, a driver feature set, and an order feature set, wherein the order feature set includes drunk-hotspot-relating features; and train a preliminary classification model based on the plurality of features and the plurality of samples to obtain a drunk model.

Classes IPC  ?

• G06N 20/00 - Apprentissage automatique
• G06F 16/28 - Bases de données caractérisées par leurs modèles, p.ex. des modèles relationnels ou objet

Abrégé

Systems, methods, and non-transitory computer-readable media can construct a simulation framework for a ride sharing service. The simulation framework comprises a simulation environment and an agent comprising one or more algorithms including an order dispatching algorithm and a driver reposition algorithm. One or more states of the simulation environment include information about a plurality of drivers and a plurality of trip order requests, and can be provided to the agent. One or more actions from the agent can be obtained. The one or more actions comprises at least one of: a plurality of matches between the plurality of drivers and the plurality of trip order requests, or a plurality of reposition destinations for a subset of the plurality of drivers. The one or more states of the simulation environment can be updated based on the one or more actions.

Classes IPC  ?

• G06F 30/27 - Optimisation, vérification ou simulation de l’objet conçu utilisant l’apprentissage automatique, p.ex. l’intelligence artificielle, les réseaux neuronaux, les machines à support de vecteur [MSV] ou l’apprentissage d’un modèle
• G06N 5/00 - Agencements informatiques utilisant des modèles fondés sur la connaissance
• G06N 20/20 - Techniques d’ensemble en apprentissage automatique
• G06Q 50/30 - Transport; Communications
• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation

Abrégé

Embodiments of the present description disclose a target discrimination method and system. The target discrimination method comprises: determining a first image sequence on the basis of a plurality of target images, the image capture time of the plurality of target images having a correspondence with the irradiation time of a plurality of lights in a lighting sequence irradiated on a target object; determining a second image sequence on the basis of a plurality of color template images, the plurality of color template images being generated on the basis of the lighting sequence; and on the basis of the first image sequence and the second image sequence, determining the authenticity of the plurality of target images.

Classes IPC  ?

• G06V 10/40 - Extraction de caractéristiques d’images ou de vidéos

Abrégé

Disclosed in the embodiments of the present description are a target identification method and system. The target identification method comprises: acquiring a plurality of target images, wherein photographing times of the plurality of target images have a correlation with irradiation times of a plurality of illuminations in an illumination sequence that are irradiated to a target object, the plurality of illuminations have a plurality of colors, the plurality of colors comprise at least one reference color and at least one verification color, and each of the at least one verification color is determined on the basis of at least some of the at least one reference color; and determining the authenticity of the plurality of target images on the basis of the illumination sequence and the plurality of target images.

Classes IPC  ?

• G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
• G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
• G06N 3/04 - Architecture, p.ex. topologie d'interconnexion
• G06N 3/08 - Méthodes d'apprentissage
• G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives

Abrégé

Disclosed in the embodiments of the present description are an image verification method, system and apparatus, and a storage medium. The image verification method comprises: instructing a terminal device to emit at least two beams of colored light to a target; during the process of emitting the at least two beams of colored light, instructing the terminal device to collect a plurality of images of the target; selecting, from the plurality of images, at least two target images that respectively correspond to the at least two beams of colored light; on the basis of the at least two target images, determining a target verification code; and performing image authenticity verification by comparing the target verification code with a reference verification code corresponding to the at least two beams of colored light.

Classes IPC  ?

• G06V 10/60 - Extraction de caractéristiques d’images ou de vidéos relative aux propriétés luminescentes, p.ex. utilisant un modèle de réflectance ou d’éclairage

Abrégé

The embodiments of the present description provide a method and system for identifying a target. The method comprises: acquiring at least one image capture parameter related to an image capture frame; sending an image capture instruction to a client, the image capture instruction instructing the client to display the image capture frame on the basis of the at least one image capture parameter; receiving at least one image from the client; and determining the authenticity of the at least one image on the basis of the at least one image capture parameter.

Classes IPC  ?

• G06F 21/32 - Authentification de l’utilisateur par données biométriques, p.ex. empreintes digitales, balayages de l’iris ou empreintes vocales

Abrégé

Method, system, and non-transitory computer-readable storage media for determining optimal resource allocation are described. An example method includes: obtaining historical data comprising a plurality of features of different system configurations, a plurality of resource consumptions of the different system configurations, and a plurality of rewards respectively generated from the different system configurations; training a plurality of neural network (NN)-based encoders respectively corresponding to the different system configurations; encoding, using the plurality of trained NN-based encoders, the plurality of features in the historical data to obtain a plurality of encoded features of the different system configurations; training a multi-armed bandit (MAB) model; and generating, using the trained MAB model, a matrix of predicted rewards, each of the predicted rewards corresponding to an estimated reward generated by allocating an amount of resources to one of the different system configurations.

Classes IPC  ?

• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
• G06Q 10/02 - Réservations, p.ex. pour billetterie, services ou manifestations
• G06N 3/08 - Méthodes d'apprentissage

Abrégé

The embodiments of the present specification disclose a method and system for target recognition. The method for target recognition comprises: determining an illumination sequence, the illumination sequence being used to determine multiple colors of multiple illuminations emitted by a terminal when irradiating a target object; acquiring multiple target images on the basis of the terminal, the image capture times of the multiple target images having a correspondence with the irradiation times of the multiple illuminations; and determining, on the basis of the illumination sequence and the multiple target images, the authenticity of the multiple target images.

Classes IPC  ?

• G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
• G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
• G06N 3/04 - Architecture, p.ex. topologie d'interconnexion
• G06N 3/08 - Méthodes d'apprentissage
• G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives

Abrégé

The present disclosure provides methods and systems for vehicle verification. The method may include receiving vehicle verification information related to a vehicle to be verified from a client, wherein the vehicle verification information includes a plurality of images acquired by the client via an imaging device, and the vehicle verification information responds to at least one vehicle verification instruction. The method may further include determining a verification result of the vehicle based on the vehicle verification information.

Classes IPC  ?

• G06V 20/50 - Contexte ou environnement de l’image
• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux

Abrégé

The application discloses Systems and methods for a data synchronization. The system may include a receiving module, an instruction generating module and a sending module. The receiving module may be configured to receive the first instruction. The first instruction may be used to instruct the start of data acquisition of the system. In response to receiving the first instruction, the instruction generating module may be configured to generate a second instruction. The second instruction may be used to trigger at least two sensors to acquire data. The sending module may be configured to send second instruction to at least two sensors respectively based on the first delay. The first delay causes the time difference between at least two sensors starting to acquire data less than the first preset threshold.

Classes IPC  ?

• H04L 12/70 - Systèmes de commutation par paquets
• H04L 67/133 - Protocoles pour les appels de procédure à distance [RPC]
• H04L 7/00 - Dispositions pour synchroniser le récepteur avec l'émetteur
• H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p.ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance

Abrégé

The embodiments of the present disclosure provide a visual positioning method, the method may include obtaining a positioning image collected by an imaging device; obtaining a three-dimensional (3D) point cloud map associated with an area where the imaging device is located; determining a target area associated with the positioning image from the 3D point cloud map based on the positioning image; and The embodiments of the present disclosure provide a visual positioning method, the method may include obtaining a positioning image collected by an imaging device; obtaining a three-dimensional (3D) point cloud map associated with an area where the imaging device is located; determining a target area associated with the positioning image from the 3D point cloud map based on the positioning image; and determining positioning information of the imaging device based on the positioning image and the target area.

Classes IPC  ?

• G06T 7/73 - Détermination de la position ou de l'orientation des objets ou des caméras utilisant des procédés basés sur les caractéristiques
• G06V 10/22 - Prétraitement de l’image par la sélection d’une région spécifique contenant ou référençant une forme; Localisation ou traitement de régions spécifiques visant à guider la détection ou la reconnaissance
• G06V 10/774 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p.ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]; Séparation aveugle de source méthodes de Bootstrap, p.ex. "bagging” ou “boosting”
• G06V 10/74 - Appariement de motifs d’image ou de vidéo; Mesures de proximité dans les espaces de caractéristiques
• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
• G06V 20/70 - RECONNAISSANCE OU COMPRÉHENSION D’IMAGES OU DE VIDÉOS Éléments spécifiques à la scène Étiquetage du contenu de scène, p.ex. en tirant des représentations syntaxiques ou sémantiques
• G06T 7/10 - Découpage; Détection de bords
• G06V 10/52 - Analyse spatiale multi-échelle, p.ex. analyse par ondelettes
• G01S 17/89 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour la cartographie ou l'imagerie

Abrégé

Systems and methods are provided for using encoded representations of numbers in various applications. The encoded representations of numbers, also referred to as number embeddings, may be multi-element data structures (e.g., multi-dimensional vectors) in which each element is a real-numbered value. The values of a given number embedding collectively encode information from which properties of the number represented by the number embedding may be derived. Number embeddings may be compared or otherwise analyzed with respect to each other to identify patterns or similarities in the numbers represented by each number embedding.

Classes IPC  ?

• G06F 17/16 - Calcul de matrice ou de vecteur
• G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p.ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
• G06N 5/04 - Modèles d’inférence ou de raisonnement
• G06N 20/00 - Apprentissage automatique

Abrégé

An interaction method and an interaction apparatus. After acquiring a path navigation information of a terminal, a server (12) determines road condition information of each road section according to a location of a target object relative to a corresponding lane of a corresponding road section in a road condition collection sequence of each road section in the previously acquired path navigation information, and after determining a target image corresponding to a road section in the road sections of which road condition information meets preset road conditions, sends the target image to the terminal. After receiving the target image, the terminal may perform, on a navigation page, rendering display on a road condition display control for displaying the target image. The location of each target object can be accurately determined by means of image recognition, and the road condition information of each road section is determined according to the location of each target object. Meanwhile, a road condition of a specific road section is displayed by means of a real scene image. Thus, the accuracy and timeliness of road condition determination are improved, such that a user can avoid a congested road section in a timely fashion.

Classes IPC  ?

• G01C 21/36 - Dispositions d'entrée/sortie pour des calculateurs embarqués
• G01C 21/20 - Instruments pour effectuer des calculs de navigation
• G01C 21/28 - Navigation; Instruments de navigation non prévus dans les groupes spécialement adaptés pour la navigation dans un réseau routier avec corrélation de données de plusieurs instruments de navigation

Abrégé

Methods and systems for off-route identification may be provided. A first navigation route of an object that is traveling and one or more positioning location points during traveling may be obtained. Whether a first preset condition is satisfied may be determined based on a positional relationship between the one or more positioning location points and the first navigation route. In response to determining that the first preset condition is not satisfied, whether the object is off-route may be determined based on information associated with the traveling of the object.

Classes IPC  ?

• G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire
• G01C 21/36 - Dispositions d'entrée/sortie pour des calculateurs embarqués

Abrégé

This disclosure describes systems and methods for repositioning vehicles. An exemplary method includes obtaining a plurality of current features associated with a vehicle located in one of the plurality of grid cells; inputting the plurality current features associated with the vehicle into a neural network; obtaining, from the neural network, a plurality of conditional action values for repositioning the vehicle to a plurality of target grid cells conditioned upon the plurality current features associated with the vehicle, wherein the plurality of target grid cells comprise the one grid cell that the vehicle is currently located in and other grid cells in the plurality of grid cells that are within two or more layers surrounding the one grid cell; and sending one or more of the plurality of target grid cells with highest conditional action values to the vehicle for repositioning.

Classes IPC  ?

• G08G 1/00 - Systèmes de commande du trafic pour véhicules routiers
• G06N 3/02 - Réseaux neuronaux
• G06F 9/30 - Dispositions pour exécuter des instructions machines, p.ex. décodage d'instructions
• G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques

Abrégé

A method of echo path delay destination and echo cancellation is described in this disclosure. The method includes: obtaining a reference signal, a microphone signal, and a trained multi-task deep neural network, wherein the multi-task deep neural network comprises a first neural network and a second neural network; generating, using the first neural network of the multi-task deep neural network, an estimated echo path delay based on the reference signal and the microphone signal; updating the reference signal based on the estimated echo path delay; and generating, using the second neural network of the multi-task deep neural network, an enhanced microphone signal based on the microphone signal and the updated reference signal.

Classes IPC  ?

• H04B 3/20 - Systèmes à ligne de transmission - Détails ouverture ou fermeture de la voie d'émission; Commande de la transmission dans une direction ou l'autre
• G10K 11/178 - Procédés ou dispositifs de protection contre le bruit ou les autres ondes acoustiques ou pour amortir ceux-ci, en général utilisant des effets d'interférence; Masquage du son par régénération électro-acoustique en opposition de phase des ondes acoustiques originales
• G06N 3/04 - Architecture, p.ex. topologie d'interconnexion
• G06N 3/08 - Méthodes d'apprentissage
• H03G 3/00 - Commande de gain dans les amplificateurs ou les changeurs de fréquence

Abrégé

A unified learning approach for large-scale ride-hailing is described, the approach includes obtaining an offline state value network for predicting a value of a vehicle state, the offline state value network being trained based on a plurality of historical vehicle trajectories; initializing an online state value network and dispatching a plurality of vehicles according to the online state value network for a period of time; training the online state value network based on vehicle states of the plurality of vehicles before and after the dispatching and rewards associated with the dispatching; ensembling the trained online state value network and the offline state value network to obtain an ensembled online state value network; and dispatching the plurality of vehicles according to the ensembled online state value network.

Classes IPC  ?

• G08G 1/00 - Systèmes de commande du trafic pour véhicules routiers
• G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
• H04L 29/08 - Procédure de commande de la transmission, p.ex. procédure de commande du niveau de la liaison
• G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques

Abrégé

A system and method of determining a policy to prevent fading drivers is described. The system and method creates virtual trajectories of incentives such as coupons offered to drivers in a transportation hailing system and corresponding states of drivers in response to the incentives. A joint policy simulator is created from an incentive policy, a confounding incentive policy, and an incentive object policy to generate the simulated actions of drivers in response to different incentives. The rewards of the simulated actions of the drivers is determined by a discriminator. The incentive policy for preventing fading drivers is optimized by reinforcement learning based on the virtual trajectories generated by the joint policy simulator and discriminator.

Classes IPC  ?

• G06N 3/08 - Méthodes d'apprentissage
• G06Q 50/30 - Transport; Communications
• G06Q 30/0211 - Détermination de l’efficacité des remises ou des incitations
• G06Q 30/0208 - Commerce ou échange de biens ou de services contre des incitations ou des récompenses
• G06Q 30/0207 - Remises ou incitations, p.ex. coupons ou rabais

Abrégé

The present disclosure relates to a method and apparatus for domain adaptation learning, and a device, a medium and a product. The method described herein comprises: acquiring a source video sample set of a source domain and a target video sample set of a target domain, wherein source video samples in the source video sample set are marked as belonging to one of a plurality of known categories; on the basis of a plurality of similarities between a plurality of target video samples in the target video sample set and the source video sample set, determining the probability of each of the plurality of target video samples belonging to an unknown category; and at least on the basis of the plurality of target video samples and the corresponding probabilities thereof, making a multi-classification model, which is previously pre-trained by using the source video sample set, adaptive to the target domain. Therefore, more reliable domain adaptation learning for video classification can be realized.

Classes IPC  ?

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

Abrégé

A system for evaluating order dispatching policy includes a first computing device, at least one processor, and a memory. The first computing device is configured to generate historical driver data associated with a driver. The at least one processor is configured to store instructions. When executed by the at least one processor, the instructions cause the at least one processor to perform operations. The operations performed by the at least one processor includes obtaining the generated historical driver data associated with the driver. Based at least in part on the obtained historical driver data, a value function is estimated. The value function is associated with a plurality of order dispatching policies. An optimal order dispatching policy is then determined. The optimal order dispatching policy is associated with an estimated maximum value of the value function. The estimation of the value function applies a feed-forward neutral network

Classes IPC  ?

• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
• G06Q 50/30 - Transport; Communications
• G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"

Abrégé

Embodiments of the disclosure provide a method for knowledge-based visual question answering, a system, and a computer program product thereof. The method includes storing the candidate supporting facts in memory slots. The method further includes generating a second visual-semantic representation for the image-question pair. The method additionally includes applying a first set of attentions over the memory slots storing the candidate supporting facts, to obtain a memory summary based on the second visual-semantic representation of the image-question pair. The method additionally includes applying a second set of attentions to generate a third visual-semantic representation of the image-question pair based on the obtained memory summary. The method additionally includes generating an updated visual-semantic representation of the image-question pair based on the third visual-semantic representation. The method additionally includes identifying a candidate supporting fact with a highest probability as a target supporting fact for the answer to the question related to the image.

Classes IPC  ?

• G06K 9/72 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques utilisant une analyse de contexte basée sur l'identité provisoire attribuée à une série de formes successives, p.ex. d'un mot
• G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques

Abrégé

A battery state of health prediction method and apparatus, and an electronic device and a readable storage medium, which relate to the technical field of computers. The method may comprise: determining, by means of a preset first correlation, the current state of health corresponding to the current driving mileage of a target electric vehicle (22); and then, on the basis of a pre-trained machine learning model and by comprehensively taking the current battery state of health, the current driving mileage and the current battery parameter into consideration, predicting a target battery state of health corresponding to a target driving mileage of the target electric vehicle (23). During a prediction process, a prediction result is more accurate by combining a current battery state of health.

Classes IPC  ?

• G01R 31/367 - Logiciels à cet effet, p.ex. pour le test des batteries en utilisant une modélisation ou des tables de correspondance

Abrégé

The disclosure relates to system and method for image quality detection. The method may include: obtaining an image acquired by a camera; obtaining an image quality detection model, the image quality detection model being provided by training a machine learning model using a plurality of training samples; determining a detection result of the image using the image quality detection model; and in response to a determination that the detection result includes a quality anomaly of the image, generating a strategy in response to the quality anomaly.

Classes IPC  ?

• G06T 7/00 - Analyse d'image
• G06V 10/422 - Extraction de caractéristiques globales par l’analyse du motif entier, p.ex. utilisant des transformations dans le domaine de fréquence ou d’autocorrélation pour représenter la structure du motif ou de la forme d’un objet à cet effet
• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux

Abrégé

The present disclosure provides methods and systems for recommending pick-up points. The method may include obtaining information of a searched point of interest determined by a user; determining a first set of candidate pick-up points based at least on the information of the searched point of interest, the first set of candidate pick-up points including a plurality of candidate pick-up points; determining at least one recommended pick-up point through a preset algorithm based at least on the first set of candidate pick-up points, and displaying the at least one recommended pick-up point to the user.

Classes IPC  ?

• H04W 4/021 - Services concernant des domaines particuliers, p.ex. services de points d’intérêt, services sur place ou géorepères
• G01C 21/00 - Navigation; Instruments de navigation non prévus dans les groupes
• G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
• H04W 4/02 - Services utilisant des informations de localisation

Abrégé

A method and apparatus for presenting road information, a device, a storage medium, and a program product. The method comprises: presenting a road visual element (184) associated with a target road (110) (402); and in response to determining that the congestion degree of the target road (110) is higher than a predetermined threshold, presenting at least one road condition image (182) in association with the road visual element (184), the at least one road condition image (182) being selected from a group of road condition images (140) that are used for determining the congestion degree, and the group of road condition images (140) being acquired by an image acquisition device (130) associated with a vehicle (120) traveling on the target road (110) (404). On the basis of this mode, more accurate road condition information can be provided for a user in a more intuitive mode.

Classes IPC  ?

• G08G 1/0967 - Systèmes impliquant la transmission d'informations pour les grands axes de circulation, p.ex. conditions météorologiques, limites de vitesse

Abrégé

The embodiments of the present disclosure relate to a method for encrypting a verification code image, and a device, a storage medium and a computer program product. The method comprises: generating an original verification code image, wherein the original verification code image corresponds to a first character string; determining scramble gradient information of the original verification code image according to a second character string, wherein the scramble gradient information comprises an adjustment gradient of each pixel in the original verification code image, and the second character string is a scramble character string of the first character string; and adjusting the original verification code image according to the scramble gradient information, so as to generate an encrypted verification code image, wherein a neural network recognition result of the encrypted verification code image is the second character string. By using the method, the security of a verification code image can be improved, thereby effectively preventing malicious registration behavior.

Classes IPC  ?

• G06F 21/36 - Authentification de l’utilisateur par représentation graphique ou iconique
• G06F 21/60 - Protection de données

Abrégé

The embodiments of the present disclosure relate to a keyboard encryption method, and a device, a storage medium and a computer program product. The method comprises: performing feature extraction on a keyboard character image, so as to determine a feature of the keyboard character image; determining a fusion feature according to the feature of the keyboard character image and a feature of a wrong keyboard character; determining an encrypted keyboard character image according to the fusion feature, wherein the wrong keyboard character is different from the character corresponding to the keyboard character image; and constructing an encrypted keyboard on the basis of the encrypted keyboard character image, wherein a neural network recognition result of the encrypted keyboard character image is a wrong keyboard character, and the encrypted keyboard character image has the same visual recognition result as the keyboard character image. By using the method, the security of a keyboard can be improved, thereby effectively preventing the occurrence of malicious registration behavior.

Classes IPC  ?

• G06F 21/60 - Protection de données
• G06F 21/83 - Protection des dispositifs de saisie, d’affichage de données ou d’interconnexion dispositifs de saisie de données, p.ex. claviers, souris ou commandes desdits claviers ou souris
• G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
• G06N 3/04 - Architecture, p.ex. topologie d'interconnexion
• G06N 3/08 - Méthodes d'apprentissage

Abrégé

A ride-sharing system can automatically and autonomously determine whether a rider is an account holder associated with an account of a ride-sharing service that requested a ride or a guest rider. A guest rider detection system can use geolocation data to determine whether a rider is a guest rider or an account holder. The system can obtain location data for an account holder that requests a ride using a ride sharing application. The location data of the account holder can be compared with one or more locations (e.g., pickup or drop off location) associated with the requested ride. Based at least in part on the comparisons between the location data of the account holder and the one or more locations associated with the requested ride, the system can determine with a particular degree of certainty whether the rider is the guest rider or the account holder.

Classes IPC  ?

• G06Q 50/30 - Transport; Communications
• G06Q 50/10 - Services
• H04W 4/02 - Services utilisant des informations de localisation
• H04W 4/60 - Services basés sur un abonnement qui utilisent des serveurs d’applications ou de supports d’enregistrement, p.ex. boîtes à outils d’application SIM

Abrégé

A navigation method and apparatus, a device, a storage medium and a program product. A method comprises: acquiring a destination position associated with a first object, wherein the destination position is also associated with a second object, and the destination position indicates a predetermined site at which the first object can meet the second object (202); determining the current position of the first object (204); and providing a navigation interface, the navigation interface comprising navigation elements superimposed on a real-scene image associated with the current position, the navigation elements being determined on the basis of the destination position and the current position (206). The present invention can provide intuitive navigation for objects to meet, thereby increasing the efficiency of meeting between objects.

Classes IPC  ?

• G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire

Abrégé

A ride-sharing system can automatically and autonomously determine whether a rider is an account holder associated with an account of a ride-sharing service that requested a ride or a guest rider. A guest rider detection system can use geolocation data to determine whether a rider is a guest rider or an account holder. The system can obtain location data for an account holder that requests a ride using a ride sharing application. The location data of the account holder can be compared with one or more locations (e.g., pickup or drop off location) associated with the requested ride. Based at least in part on the comparisons between the location data of the account holder and the one or more locations associated with the requested ride, the system can determine with a particular degree of certainty whether the rider is the guest rider or the account holder.

Classes IPC  ?

• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation

Abrégé

Systems and methods for registering point clouds are provided. An exemplary method includes parsing semantic information from source and target point clouds, segmenting points in the source point cloud into first and second groups based on the semantic information, segmenting points in the target point cloud into third and fourth groups based on the semantic information, determining an initial pose of the source point cloud by registering the first group of points in the source point cloud to the third group of points in the target point cloud according to a first resolution, and adjusting the initial pose of the source point cloud by registering the second group of points in the source point cloud to the fourth group of points in the target point cloud according to a second resolution, wherein the second resolution is different from the first resolution.

Classes IPC  ?

• G06T 7/30 - Détermination des paramètres de transformation pour l'alignement des images, c. à d. recalage des images
• G06T 7/10 - Découpage; Détection de bords
• G06T 7/70 - Détermination de la position ou de l'orientation des objets ou des caméras

Abrégé

Embodiments of the disclosure provide systems and methods for detecting road markings from a laser intensity image. An exemplary method may include receiving, by a communication interface, the laser intensity image acquired by a sensor. The method may also include segmenting the laser intensity image into a plurality of road segments, and dividing a road segment into a plurality of sub-images. The method may further include generating a road marking image corresponding to each of the sub-images based on a semantic segmentation method using a learning model and generating an overall road marking image for the road segment by piecing together the road marking images corresponding to the sub-images of the road segment.

Classes IPC  ?

• G06V 20/10 - Scènes terrestres
• G06V 10/26 - Segmentation de formes dans le champ d’image; Découpage ou fusion d’éléments d’image visant à établir la région de motif, p.ex. techniques de regroupement; Détection d’occlusion
• G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p.ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersections; Analyse de connectivité, p.ex. de composantes connectées
• G06V 10/20 - Prétraitement de l’image
• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux

Abrégé

The embodiments of the present description relate to a method and apparatus for optimizing a journey of a user, an electronic device, a storage medium, and a computer program product. In the method, a desired drop-off place for a journey by a user is determined. If it is determined that the desired drop-off place is located at a no-stop road section, a new drop-off place for the journey is determined. Then, instead of the desired drop-off place, a new candidate drop-off place is displayed to the user and an indication relating to the desired drop-off place being located at a no-stop road section is displayed. Further provided are a corresponding apparatus, an electronic device, and a storage medium. By using the described implementation means, it is possible to optimize the journey of a user by displaying a new drop-off place to the user instead of a desired drop-off place.

Classes IPC  ?

• G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
• G06F 16/9537 - Recherche à dépendance spatiale ou temporelle, p.ex. requêtes spatio-temporelles

Abrégé

Provided in embodiments of the present description are a method and apparatus for use in recommending a pickup spot, a device, a medium, and a program product. The method provided comprises: providing a first position located in a stopping-permitted road section to a service requester as a target pickup spot; if a determination is made that the service requester attempts to change the target pickup spot from the first position to a second position located in a stopping-prohibited road section, automatically changing the target pickup spot to a third position located in a stopping-permitted road section; and providing a stopping-prohibited prompt regarding stopping-prohibited road sections to the service requester. By such means, the service requester could easily understand and accept the transfer of the target pickup spot to a safe stopping-permitted zone.

Classes IPC  ?

• G06F 16/9537 - Recherche à dépendance spatiale ou temporelle, p.ex. requêtes spatio-temporelles

Abrégé

Provided in the embodiments of the present description are a method, apparatus, and device for use in prompting a no-parking road section, a computer-readable storage medium, and a computer program product, applicable in the field of intelligent traffic. The method of the present description comprises: determining a stop associated with a trip; determining a set of no-parking road sections in the vicinity of the stop; and if the distance between a transport and at least one no-parking road section in the set of no-parking road sections is determined to be less than a first threshold distance, issuing a prompt related to the set of no-parking road sections by means of a terminal associated with the trip. The embodiments of the present description effectively reduce the probability of a user parking illegally, thus enhancing user experience.

Classes IPC  ?

• G06F 16/9537 - Recherche à dépendance spatiale ou temporelle, p.ex. requêtes spatio-temporelles
• G06F 16/9538 - Présentation des résultats des requêtes
• G06F 16/29 - Bases de données d’informations géographiques
• G06Q 50/30 - Transport; Communications
• G06Q 50/26 - Services gouvernementaux ou services publics

Abrégé

A system for evaluating order dispatching policy includes a first computing device, at least one processor, and a memory. The first computing device is configured to generate historical driver data associated with a driver. The at least one processor is configured to store instructions. When executed by the at least one processor, the instructions cause the at least one processor to perform operations. The operations performed by the at least one processor includes obtaining the generated historical driver data associated with the driver. Based at least in part on the obtained historical driver data, a value function is estimated. The value function is associated with a plurality of order dispatching policies. An optimal order dispatching policy is then determined. The optimal order dispatching policy is associated with an estimated maximum value of the value function. The estimation of the value function applies a cerebellar model arithmetic controller.

Classes IPC  ?

• G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire
• B60W 40/09 - Style ou comportement de conduite

Abrégé

A method and apparatus for optimizing a boarding point, a device, a medium, and a program product. The method proposed therein comprises determining a target boarding point of a service requester (110), a service provider (120) needing to arrive at the target boarding point to pick up the service requester (110); determining whether the target boarding point is located on a parking restriction road section; and if determining that the target boarding point is located on the parking restriction road section, providing prompt information for the service requester (110) on the basis of relative positioning states of the service provider (120) and the target boarding point, the prompt information at least comprising parking restriction information for indicating the parking restriction characteristics of the target boarding point. According to the method, by indicating the service requester (110) with the parking restriction characteristics, the service requester (110) can be guided to board as soon as possible within a reasonable time, such that a dwell time of a vehicle of the service provider (120) on the parking restriction road section can be avoided, thereby avoiding the triggering of a parking restriction penalty on the road section, and ensuring smooth and safe road traffic.

Classes IPC  ?

• G06F 16/29 - Bases de données d’informations géographiques

Abrégé

A method for identity risk assessment may include receiving a target identity (ID) verification event of a first user account from a user terminal, the target ID verification event including a target ID number. The method may also include obtaining a first feature associated with the first user account and a second feature associated with the target ID number based on the target ID verification event. The method may also include determining whether the target ID verification event is a malicious ID verification event using a risk assessment model to analyze the first feature and the second feature. In response to determining that the target ID verification event is a malicious ID verification event, the method may further include blocking at least one of the first user account and the target ID number.

Classes IPC  ?

• H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole

Abrégé

A method, an apparatus, a device, and a medium for use in data processing. The method comprises: acquiring a target image associated with a target object, the target image having spots, the spots being generated by the target object reflecting a laser beam of a specific wavelength (210); determining from the target image a target sub-image associated with a specific part of the target object (220); and performing a living body detection with respect to the target object on the basis of the target sub-image (230). By such means, whether the target object is a live user can be determined accurately and efficiently.

Classes IPC  ?

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

Abrégé

A method may include receiving a service request; obtaining a route linking the starting location and the destination; obtaining one or more global features associated with the service request; using a first model to analyze the one or more global features associated with the service request to produce a global vector for the service request; using a second model to analyze the features of each of the road segment to produce a local segment vector for each of the road segments; determining a segment weight of the global vector for each road segment based on the global vector and its corresponding local segment vector; obtaining a global segment vector for each road segment based on its corresponding segment weight and the global vector; obtaining a segment vector for each road segment by combining its corresponding local and global segment vectors; obtaining the ETA for the service request based on the segment vectors.

Classes IPC  ?

• G01C 21/00 - Navigation; Instruments de navigation non prévus dans les groupes
• G01C 21/30 - Mise en coïncidence avec des cartes ou des contours

Abrégé

A computer-implemented method for determining incentive distribution includes: obtaining, by a computing device, a computer model, the computer model being configured to: obtain state information of a user of a platform and an incentive action of the platform, and generate simulation results on at least one performance criterion of the platform with and without the incentive action being provided to the user; receiving a computing request comprising state information of one or more visiting users; determining, by feeding the state information and the incentive action to the computer model, an uplift on the at least one performance criterion by providing the incentive action. By evaluating the uplift effect based on statistical distribution of the order and reward, the activeness of the user, and counter-factual balance of the data, the method improves the accuracy of the uplift prediction, thereby improving efficiency and accuracy of the incentive distribution.

Classes IPC  ?

• G06Q 30/02 - Marketing; Estimation ou détermination des prix; Collecte de fonds

Abrégé

Systems and methods for training an initial machine learning model is provided. The system may train an initial machine learning model using source domain training data with sample labels and target domain training data without sample labels. The initial machine learning model may include a feature extraction unit, a first processing unit, and an adversarial unit, wherein the first processing unit is associated with a first loss function, and the adversarial unit is associated with a second loss function. In some embodiments, the initial machine learning model may also include a second processing unit. A third loss function that reflects the consistency of the first processing unit and the second processing unit may be determined. The initial machine learning model may be trained based on the feature extraction unit, the first processing unit, the adversarial unit, and the second processing unit.

Classes IPC  ?

• G06N 20/20 - Techniques d’ensemble en apprentissage automatique
• G06N 3/08 - Méthodes d'apprentissage
• G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques

Abrégé

A method includes: selecting a current discount strategy according to a simulation result of a simulator of a machine learning model, wherein the simulation result comprises simulations of future transportation order bubbling in response to discounts given to current transportation order bubbling; obtaining a plurality of bubbling features of a transportation plan of a user, wherein the plurality of bubbling features comprise (i) a bubble signal comprising time information and location information corresponding to the transportation plan (ii) a supply and demand signal comprising transportation supply-demand information corresponding to the transportation plan, and (iii) a transportation order history signal of the user; determining a discount signal according to the plurality of bubbling features and the current discount strategy; and transmitting the discount signal to a computing device of the user.

Classes IPC  ?

• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
• G06Q 50/30 - Transport; Communications
• G06N 20/00 - Apprentissage automatique

Abrégé

A computer-implemented method includes: obtaining a model comprising an environment module, a resource allocation module, and a personal recommendation module, receiving a real-time online signal of visiting the platform from a computing device of a visiting user; determining a resource allocation action by feeding user contextual data of the visiting user to the model; and based on the determined resource allocation action, transmitting a return signal to the computing device to present the resource allocation action.

Classes IPC  ?

• G06N 3/04 - Architecture, p.ex. topologie d'interconnexion
• G06Q 30/00 - Commerce

Abrégé

Systems and methods are disclosed configured to receive a ride request from an application hosted on a device of a user. A vehicle is routed to a pickup location. A route is generated configured to navigate the vehicle to a destination. Sensor data indicative of ride quality is monitored while the vehicle is navigating the generated route, wherein the sensor data comprises data indicating at least how bumpy the ride is and/or whether a sudden braking event occurred. When an adverse ride condition is detected, a determination is made that a content item is to be transmitted to a display device. A geofence is generated about the destination using a user content interaction history. The first item of content is selected based at least in part on an identification of an establishments within the geofence. The selected item of content is transmitted to the display device and the user may be transported to the pickup location within the geofence.

Classes IPC  ?

• G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire
• G01C 21/36 - Dispositions d'entrée/sortie pour des calculateurs embarqués
• G06Q 50/30 - Transport; Communications

Abrégé

Multi-objective distributional reinforcement learning may be applied to order dispatching on ride-hailing platforms. A set of historical driver trajectories and a set of driver-order pairs may be obtained. A weight vector between a first reward of the set of historical driver trajectories and a second reward of the set of historical driver trajectories may be determined using inverse reinforcement learning (IRL). A first value function and a second value function may be jointly learned using distributional reinforcement learning (DRL) based on the historical driver trajectories and the weight vector. A set of scores comprising a score of each driver-order pair in the set of driver-order pairs may be determined based on the weight vector, the first value function, and the second value function. A set of dispatch decisions may be determined based on the set of scores that maximizes a total reward of the set of dispatch decisions.

Classes IPC  ?

• G06Q 30/02 - Marketing; Estimation ou détermination des prix; Collecte de fonds
• G06Q 50/30 - Transport; Communications
• G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire

Abrégé

The present disclosure provides a system for improving security. The system may identify a query associated with a user account, and access an ID graph database to obtain an ID graph relating to the user account by a database driver. The system may also determine whether the user account is a target account type based at least on the ID graph. The ID graph may include a plurality of nodes and a plurality of edges. Each of the plurality of edges may connect two nodes. Each of the plurality of nodes may include at least one of a register ID, a login ID, a payment ID, a background check ID, or a face ID. Each edge that connects two nodes may include at least one of a user type associated with the two nodes, a timestamp when the edge is connected, or source information of the edge.

Classes IPC  ?

• H04L 9/40 - Protocoles réseaux de sécurité
• G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation
• G06N 20/00 - Apprentissage automatique

Abrégé

An automatic agent may be improved through feedback. A user input may be received through a user interface. A plurality of current utterance variables may be obtained by tokenizing the user input. The automatic agent may execute a machine learning policy to generate a reply to the user input based on the plurality of current utterance variables. A different reply may be obtained in response to an indication that the reply will lead to a breakdown, wherein the breakdown comprises an unhuman response from the automatic agent according to the machine learning policy. The machine learning policy may be adjusted based on the plurality of current utterance variables and the different reply.

Classes IPC  ?

• G10L 15/06 - Création de gabarits de référence; Entraînement des systèmes de reconnaissance de la parole, p.ex. adaptation aux caractéristiques de la voix du locuteur
• G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p.ex. dialogue homme-machine 
• G06F 3/16 - Entrée acoustique; Sortie acoustique
• G10L 15/01 - Estimation ou évaluation des systèmes de reconnaissance de la parole
• G06F 40/56 - Génération de langage naturel
• G06N 20/00 - Apprentissage automatique
• G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur

Abrégé

Systems and methods are disclosed configured to receive a ride request from an application hosted on a device of a user. A vehicle is routed to a pickup location. A route is generated configured to navigate the vehicle to a destination. Sensor data indicative of ride quality is monitored while the vehicle is navigating the generated route, wherein the sensor data comprises data indicating at least how bumpy the ride is and/or whether a sudden braking event occurred. When an adverse ride condition is detected, a determination is made that a content item is to be transmitted to a display device. A geofence is generated about the destination using a user content interaction history. The first item of content is selected based at least in part on an identification of an establishments within the geofence. The selected item of content is transmitted to the display device and the user may be transported to the pickup location within the geofence.

Classes IPC  ?

• G06Q 30/00 - Commerce
• G06Q 30/02 - Marketing; Estimation ou détermination des prix; Collecte de fonds
• G06N 3/06 - Réalisation physique, c. à d. mise en œuvre matérielle de réseaux neuronaux, de neurones ou de parties de neurone
• H04W 4/021 - Services concernant des domaines particuliers, p.ex. services de points d’intérêt, services sur place ou géorepères
• H04W 4/02 - Services utilisant des informations de localisation
• G07C 5/08 - Enregistrement ou indication de données de marche autres que le temps de circulation, de fonctionnement, d'arrêt ou d'attente, avec ou sans enregistrement des temps de circulation, de fonctionnement, d'arrêt ou d'attente
• G01C 21/36 - Dispositions d'entrée/sortie pour des calculateurs embarqués

Abrégé

Systems and methods for map construction. The systems may include a processing circuit connected to a first sensor and a second sensor. The systems may perform the methods to receive first data including location-orientation information of a vehicle obtained by the first sensor (610); receive second data including road-surroundings information of the vehicle obtained by the second sensor (620); correct the first data based on the second data (630); and construct a map based on the corrected first data and the second data (640).

Classes IPC  ?

• G01C 21/32 - Structuration ou formatage de données cartographiques
• G01S 17/89 - Systèmes lidar, spécialement adaptés pour des applications spécifiques pour la cartographie ou l'imagerie

Abrégé

Methods, systems, and apparatus, including computer programs encoded on computer storage media for task control based on Bayesian Meta-Reinforcement learning. An exemplary method includes obtaining a base machine learning (ML) model trained based on historical data collected from historical tasks. The base ML model represents a prior distribution of model parameters in a neural network representing control policies. The exemplary method further includes receiving observed data from a new control task; training a task-level ML model based on the base ML model and the observed data, wherein the task-level ML model represents a posterior distribution of the model parameters; sampling, based on the posterior distribution of the model parameters, a set of the model parameters that represent a control policy; and applying the control policy in performing the new control task.

Classes IPC  ?

• G06N 3/08 - Méthodes d'apprentissage

Abrégé

Deep reinforcement learning may be used for vehicle repositioning on mobility-on-demand platforms. Information may be obtained. The information may include a current location of a vehicle on a ride-sharing platform. A set of paths originated from the current location of the vehicle may be obtained. Each of the set of paths may have a length less than a preset maximum path length. A set of expected cumulative rewards along the set of paths may be obtained based on a trained deep value-network. A best path from the set of paths may be selected based on a heuristic tree search of the set of expected cumulative rewards. A next step along the best path may be recommended as a reposition action for the vehicle.

Classes IPC  ?

• G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire
• G06N 3/08 - Méthodes d'apprentissage

Abrégé

Systems and methods are disclosed configured to identify a location where current or predicted ride requests exceed a threshold within a time period. Driver location information for one or more drivers is used to identify a driver to satisfy the identified current or predicted ride requests at the location that exceed the threshold within the time period. In response to determining that a driver has at least a first likelihood of accepting a ride request at the location within the time period, item content is selected using a history of establishments frequented by the driver. The selected item of content, associated with a token, is provided for presentation on a display to the driver. In response to determining that the identified driver accepted the ride request at the location within the time period, the token is enabled to be utilized by the identified driver at an entity.

Classes IPC  ?

• G06Q 30/00 - Commerce
• G06Q 30/02 - Marketing; Estimation ou détermination des prix; Collecte de fonds
• G06Q 50/30 - Transport; Communications
• G06Q 10/02 - Réservations, p.ex. pour billetterie, services ou manifestations

Abrégé

The present disclosure provides a system for improving security. The system may identify a query associated with a user account, and access an ID graph database to obtain an ID graph relating to the user account by a database driver. The system may also determine whether the user account is a target account type based at least on the ID graph. The ID graph may include a plurality of nodes and a plurality of edges. Each of the plurality of edges may connect two nodes. Each of the plurality of nodes may include at least one of a register ID, a login ID, a payment ID, a background check ID, or a face ID. Each edge that connects two nodes may include at least one of a user type associated with the two nodes, a timestamp when the edge is connected, or source information of the edge.

Classes IPC  ?

• G06Q 30/00 - Commerce

Abrégé

Methods, systems, and apparatus, including computer programs encoded on computer storage media for task control based on Bayesian Meta-Reinforcement learning. An exemplary method includes obtaining a base machine learning (ML) model trained based on historical data collected from historical tasks. The base ML model represents a prior distribution of model parameters in a neural network representing control policies. The exemplary method further includes receiving observed data from a new control task; training a task-level ML model based on the base ML model and the observed data, wherein the task-level ML model represents a posterior distribution of the model parameters; sampling, based on the posterior distribution of the model parameters, a set of the model parameters that represent a control policy; and applying the control policy in performing the new control task.

Classes IPC  ?

• G08G 1/081 - Commande des signaux de trafic plusieurs carrefours dépendant d'une commande commune
• G08G 1/01 - Détection du mouvement du trafic pour le comptage ou la commande
• G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
• G06N 3/08 - Méthodes d'apprentissage

Abrégé

The present disclosure relates to a system and a method for performing instance segmentation based on semantic segmentation that is capable of (1) processing HD images in real-time given semantic segmentation; 2) delivering comparable performance with Mask R-CNN in terms of accuracy when combined with a widely-used semantic segmentation method (such as DPC), while consistently outperforms a state-of-the-art real-time solution; (3) working flexibly with any semantic segmentation model for instance segmentation; (4) outperforming Mask R-CNN if the given semantic segmentation is sufficiently good; and (5) being easily extended to panoptic segmentation.

Classes IPC  ?

• G06T 7/10 - Découpage; Détection de bords
• G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p.ex. des objets vidéo
• G06N 3/08 - Méthodes d'apprentissage

Abrégé

A ride-sharing system can automatically and autonomously identify connections of a user by accessing one or more third-party networking services used by the user. Further, the system can determine which of the connections of the user spend at least a threshold amount of time in a geographic area where the user spends time, such as a residential area or workplace of the user. When a user requests a ride-share pool ride, the ride may be scheduled with a connection of the user improving the safety of the ride. Machine learning models may be used to predict the likelihood that a connection of the user will travel along the same route as the user and will improve the safety of the rider.

Classes IPC  ?

• G06Q 50/30 - Transport; Communications
• H04W 4/029 - Services de gestion ou de suivi basés sur la localisation
• H04W 4/08 - Gestion des groupes d'utilisateurs
• G06N 20/00 - Apprentissage automatique

Abrégé

An automatic agent may be trained using reinforcement learning. A secret task may be obtained for a simulated user, and the secret task may be unknown to the automatic agent. At least one instruction to complete the secret task may be obtained from the simulated user according to at least one RL policy. At least one action may be generated by the automatic agent based on the at least one instruction and the at least one RL policy. Rewards may be determined for the simulated user and the automatic agent in response to determining that the at least one action successfully completes the secret task. The at least one RL policy may be adjusted based on the determined rewards.

Classes IPC  ?

• G06F 9/48 - Lancement de programmes; Commutation de programmes, p.ex. par interruption
• G06N 20/00 - Apprentissage automatique
• G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
• G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p.ex. dialogue homme-machine 
• G06F 9/38 - Exécution simultanée d'instructions
• G06F 9/54 - Communication interprogramme

Abrégé

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for constructing a virtual environment for a ride-hailing platform are disclosed. An exemplary method comprises: obtaining a plurality of historical interaction trajectories each comprising one or more interaction records between a driver and a ride-hailing platform, each interaction record comprising a program recommendation of the ride-hailing platform to the driver and a reaction of the driver in response to the program recommendation; training a simulator based on the plurality of historical interaction trajectories; and integrating a reward function with the simulator to construct the virtual environment, wherein the plurality of first program recommendations and the plurality of reactions form a plurality of simulated interactions, and a data distribution of the plurality of simulated interactions approximates a data distribution of a plurality of interaction records in the plurality of historical interaction trajectories.

Classes IPC  ?

• G06Q 50/30 - Transport; Communications
• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
• G06Q 30/02 - Marketing; Estimation ou détermination des prix; Collecte de fonds
• G06N 20/00 - Apprentissage automatique

Abrégé

A system for pick-up location recommendation is provided. The system may receive a start location of a service order from a requester terminal, and determine a plurality of candidate pick-up locations around the start location base on a location information database. Each candidate pick-up location may have a relative position to a boundary of the start location. The system may determine one or more recommended pick-up locations among the plurality of candidate pick-up locations by applying a pick-up location recommendation model to the plurality of candidate pick-up locations. An input of the pick-up location recommendation model at least may include the relative positions of the candidate pick-up locations to the boundary of the start location. The system may further transmit the one or more recommended pick-up locations to the requester terminal for recommendation.

Classes IPC  ?

• G06F 16/9537 - Recherche à dépendance spatiale ou temporelle, p.ex. requêtes spatio-temporelles

Abrégé

The present disclosure relates to systems and methods for recommending pick-up locations. The method may include obtaining and storing a current location of the user, a plurality of historical locations associated with the current location of the user, and one or more potential pick-up locations corresponding to each of the plurality of historical locations of the user. The method may also include extracting feature data from the current location, the plurality of historical locations, and the one or more potential pick-up locations corresponding to each of the plurality of historical locations of the user. The method may further include inputting the extracted feature data into a pick-up location recommendation model to determine a transition probability for each potential pick-up location. The method may still include determining a recommended pick-up location for the user based on the determined transition probability for each potential pick-up location.

Classes IPC  ?

• G06Q 30/06 - Transactions d’achat, de vente ou de crédit-bail
• G06F 16/9537 - Recherche à dépendance spatiale ou temporelle, p.ex. requêtes spatio-temporelles

Abrégé

A system and method for concurrent multi-path processing of audio signals for automatic speech recognition is presented. Audio information defining a set of audio signals may be obtained (502). The audio signals may convey mixed audio content produced by multiple audio sources. A set of source-specific audio signals may be determined by demixing the mixed audio content produced by the multiple audio sources. Determining the set of source-specific audio signals may comprises providing the set of audio signals to both a first signal processing path and a second signal processing path (504). The first signal processing path may determine a value of a demixing parameter for demixing the mixed audio content (506). The second signal processing path may apply the value of the demixing parameter to the individual audio signals of the set of audio signals (508) to generate the individual source-specific audio signals (510).

Classes IPC  ?

• G10L 15/00 - Reconnaissance de la parole
• G10L 21/18 - Transformation de la parole en une représentation non audible, p.ex. visualisation de la parole ou traitement de la parole pour les aides tactiles - Détails du procédé de transformation
• G10L 19/02 - Techniques d'analyse ou de synthèse de la parole ou des signaux audio pour la réduction de la redondance, p.ex. dans les vocodeurs; Codage ou décodage de la parole ou des signaux audio utilisant les modèles source-filtre ou l’analyse psychoacoustique utilisant l'analyse spectrale, p.ex. vocodeurs à transformée ou vocodeurs à sous-bandes
• G10L 25/18 - Techniques d'analyses de la parole ou de la voix qui ne se limitent pas à un seul des groupes caractérisées par le type de paramètres extraits les paramètres extraits étant l’information spectrale de chaque sous-bande

Abrégé

Embodiments of the disclosure provide systems and methods for verifying digital payments for a payment platform. The system includes a communication interface configured to receive service data associated with a transaction from a terminal device associated with a user of the payment platform. The system further includes at least one processor configured to automatically determine whether an authentication is waived for the transaction based on the received service data and a blacklist generated using a machine learning model. The blacklist includes a list of suspicious users and transaction behaviors. The at least one processor further configured to approve the transaction without requesting user authentication information from the terminal device when the authentication is waived. The at least one processor also configured to request the user authentication information from the terminal device and validate the user authentication information when the authentication is not waived.

Classes IPC  ?

• G06Q 30/00 - Commerce
• G06Q 10/10 - Bureautique; Gestion du temps
• G06Q 20/40 - Autorisation, p.ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasin; Examen et approbation des payeurs, p.ex. contrôle des lignes de crédit ou des listes négatives
• G06Q 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p.ex. une autorité de certification, un notaire ou un tiers de confiance
• G06N 20/00 - Apprentissage automatique
• G06F 21/31 - Authentification de l’utilisateur
• G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
• G06Q 50/26 - Services gouvernementaux ou services publics
• G06Q 40/02 - Opérations bancaires, p.ex. calcul d'intérêts ou tenue de compte

Abrégé

The present disclosure relates to systems and methods for displaying one or more points of interest (POIs) of a location-based service (LBS). The method may include receiving a request for an LBS sent by a user via a user terminal and obtaining a start location based on the request for the LBS. The method may also include determining one or more recommended POIs based on the start location and POI data associated with the start location. Further, the method may also include transmitting signals to the user terminal to display at least one of the one or more recommended POIs.

Classes IPC  ?

• G06F 16/29 - Bases de données d’informations géographiques

Abrégé

The embodiments of the present description provide an ultra-wideband-based positioning method and apparatus, an electronic device and a readable storage medium, relating to the technical field of computers. In the embodiments of the present description, as a short-range wireless communication connection is not easily disturbed, a first device and a second device can determine an accurate relative position on the basis of the short-range wireless communication connection, when the absolute position corresponding to the first device or the second device is not accurate (for example, when a position is determined by means of satellite positioning, a satellite positioning point may be inaccurate due to a weak satellite signal), the first device or the second device can determine the position of the other party according to the accurate relative position. In an application scenario of online ride-hailing, by means of the embodiments of the present description, an online ride-hailing driver and a passenger can find each other quickly.

Classes IPC  ?

• H04W 4/02 - Services utilisant des informations de localisation
• G01S 5/02 - Localisation par coordination de plusieurs déterminations de direction ou de ligne de position; Localisation par coordination de plusieurs déterminations de distance utilisant les ondes radioélectriques

Abrégé

An artificial intelligence system for detecting a transportation service related safety issue. The system includes a storage device configured to store a first sample description of an incident and a known safety issue of the incident. The first sample description includes first set of labeled texts. The system further includes at least one processor. The at least one processor is configured to segment the first sample description into word segments, determine word vectors of the respective word segments and determine features of the first set of labeled texts in the first sample description. The at least one processor is also configured to train the learning model based on the word vectors and the features. The system also includes a communication interface configured to provide the learning model for automatically detecting the transportation service related safety issue from an incident description.

Classes IPC  ?

• G06F 16/35 - Groupement; Classement

Abrégé

Methods, systems, and apparatus, including computer programs encoded on computer storage media for acoustic echo cancellation and suppression are provided. An exemplary method comprises receiving a far-end acoustic signal and a corrupted near-end acoustic signal, wherein the corrupted near-end acoustic signal is generated based on (1) an echo of the far-end acoustic signal and (2) a near-end acoustic signal; feeding the far-end acoustic signal and the corrupted near-end acoustic signal into a neural network as an input to output a time-frequency (TF) mask that suppresses the echo and retains the near-end acoustic signal, and generating an enhanced version of the corrupted near-end acoustic signal by applying the obtained TF mask to the corrupted near-end acoustic signal.

Classes IPC  ?

• G10L 21/02 - Amélioration de l'intelligibilité de la parole, p.ex. réduction de bruit ou annulation d'écho
• G06N 3/02 - Réseaux neuronaux

Abrégé

Systems and methods involving obtaining point cloud data from one or more sources corresponding to one or more zones within a real-world space, the point cloud data representing surface features of structures detected within the one or more zones; defining a plurality of first-level nodes based on the point cloud data, individual first-level nodes corresponding to obtained point cloud data corresponding to individual zones of the one or more zones; identifying connections between two or more first-level nodes, the connections between the two or more first-level nodes based on connections between the point cloud data for the zones corresponding to the two or more first-level nodes; and defining a plurality of second-level nodes, individual second-level nodes corresponding to aggregated subsets of first-level nodes for which connections are identified.

Classes IPC  ?

• G01C 21/00 - Navigation; Instruments de navigation non prévus dans les groupes
• G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire

Abrégé

A method includes: obtaining a plurality of first signals corresponding to a vehicle and a plurality of second signals corresponding to a plurality of candidate carpool combinations each comprising one or more unassigned transportation orders, wherein: the plurality of first signals comprise a current time, a location of the vehicle at the current time, and one or more static features corresponding to the vehicle, the plurality of second signals comprise timestamps, origins, and destinations of the unassigned transportation orders, and the vehicle has an on-going transportation order at the current time; inputting the plurality of first and second signals to a trained machine learning model; and obtaining, from an output of the trained machine learning model, a utility score of each of the plurality of candidate carpool combinations.

Classes IPC  ?

• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation

Abrégé

A method includes: obtaining a plurality of first signals corresponding to a vehicle and a plurality of second signals corresponding to a plurality of candidate carpool combinations each comprising one or more unassigned transportation orders, wherein: the plurality of first signals comprise a current time, a location of the vehicle at the current time, and one or more static features corresponding to the vehicle, the plurality of second signals comprise timestamps, origins, and destinations of the unassigned transportation orders, and the vehicle has an on-going transportation order at the current time; inputting the plurality of first and second signals to a trained machine learning model; and obtaining, from an output of the trained machine learning model, a utility score of each of the plurality of candidate carpool combinations.

Classes IPC  ?

• G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
• G08G 1/00 - Systèmes de commande du trafic pour véhicules routiers
• G06N 3/04 - Architecture, p.ex. topologie d'interconnexion
• G06N 3/049 - Réseaux neuronaux temporels, p.ex. éléments à retard, neurones oscillants ou entrées impulsionnelles
• G06Q 50/30 - Transport; Communications

Abrégé

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for managing user intervention for a vehicle are provided. One of the methods includes: receiving an instruction to initiate an intervention session from a server, and providing, in response to receiving the instruction, a user interface associated with the intervention session for display on a terminal associated with the vehicle. The method further includes detecting, at the terminal, a user interaction corresponding to a command associated with operation of the vehicle, and generating a decision associated with the operation of the vehicle based at least in part on the command.

Classes IPC  ?

• B60W 50/10 - Interprétation des requêtes ou demandes du conducteur
• B60W 50/14 - Moyens d'information du conducteur, pour l'avertir ou provoquer son intervention
• B60W 50/00 - COMMANDE CONJUGUÉE DE PLUSIEURS SOUS-ENSEMBLES D'UN VÉHICULE, DE FONCTION OU DE TYPE DIFFÉRENTS; SYSTÈMES DE COMMANDE SPÉCIALEMENT ADAPTÉS AUX VÉHICULES HYBRIDES; SYSTÈMES D'AIDE À LA CONDUITE DE VÉHICULES ROUTIERS, NON LIÉS À LA COMMANDE D'UN SOUS-ENSEMBLE PARTICULIER - Détails des systèmes d'aide à la conduite des véhicules routiers qui ne sont pas liés à la commande d'un sous-ensemble particulier
• G05D 1/00 - Commande de la position, du cap, de l'altitude ou de l'attitude des véhicules terrestres, aquatiques, aériens ou spatiaux, p.ex. pilote automatique
• G05D 1/02 - Commande de la position ou du cap par référence à un système à deux dimensions

Abrégé

Methods, systems, and apparatus, including computer programs encoded on computer storage media for carpool dual-pricing in ridesharing are provided. An exemplary method comprises: obtaining a machine-learning model trained to generate a probability for a carpool request from a rider to convert to a trip based at least on a pair of price adjustment multipliers applied to the carpool request; determining one or more Key Performance Indicator (KPI) models based on the machine-learning model; constructing an optimization model based on the KPI models, the optimization model comprising a plurality of pairs of price adjustment multipliers as decision variables; and determining optimal values of the plurality of pairs of price adjustment multipliers for the plurality of pricing units by solving the optimization model based on a plurality of historical carpool requests.

Classes IPC  ?

• G06Q 10/02 - Réservations, p.ex. pour billetterie, services ou manifestations
• G06N 7/00 - Agencements informatiques fondés sur des modèles mathématiques spécifiques
• G06Q 30/02 - Marketing; Estimation ou détermination des prix; Collecte de fonds
• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
• G06Q 50/30 - Transport; Communications
• G06N 20/00 - Apprentissage automatique
• G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
• G06Q 30/08 - Ventes aux enchères

Abrégé

Methods, systems, and apparatus, including computer programs encoded on computer storage media for carpool dual-pricing in ridesharing are provided. An exemplary method comprises: determining an expected trip count based on a plurality of carpool requests in a pricing unit and a pair of price adjustment multipliers applied to the pricing unit; for each of the plurality of carpool requests, generating a carpool matching probability of the carpool request by a second machine learning model based on the first expected trip count; constructing one or more Key Performance Indicator (KPI) models based on the plurality of carpool matching probabilities and the pair of price adjustment multipliers; and determining optimal values of the pair of price adjustment multipliers based on an optimization model maximizing an aggregated value of the one or more KPI models.

Classes IPC  ?

• G06Q 30/0283 - Estimation ou détermination de prix
• G06Q 30/0201 - Modélisation du marché; Analyse du marché; Collecte de données du marché
• G06Q 10/02 - Réservations, p.ex. pour billetterie, services ou manifestations
• G06Q 10/0639 - Analyse des performances des employés; Analyse des performances des opérations d’une entreprise ou d’une organisation
• G06Q 50/30 - Transport; Communications
• G06N 20/00 - Apprentissage automatique
• G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
• G06Q 30/08 - Ventes aux enchères
• G06N 7/01 - Modèles graphiques probabilistes, p.ex. réseaux probabilistes

Abrégé

A floating window control method and system. The method comprises: obtaining a first operation of a user on a terminal device, the first operation being used for instructing the terminal device to execute a first application program in the background; when the first application program is executed in the background, automatically adding a first floating window on a display interface of the terminal device, the first floating window comprising a first state and a second state, when the first floating window is in the first state, the first floating window being hidden in the display interface, and when the first floating window is in the second state, the first floating window being displayed on the display interface; and after the first floating window is added, adding a second floating window associated with the first application program, the second floating window covering a local area of the display interface, and when the relative position relationship between the second floating window and the first floating window meeting a first preset condition, the first floating window being switched from the first state to the second state, wherein the first floating window is used for closing the second floating window.

Classes IPC  ?

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

Abrégé

The present disclosure relates to systems and methods for displaying vehicle information for an on-demand service. The method may include sending a request for on-demand service to a server. The method may further include obtaining information of a vehicle related to the request for on-demand service. The information of the vehicle may include color information of the vehicle. The method may further include generating, by a processor, a user interface based on the information of the vehicle. The user interface may include at least one user interface element corresponding to the color information of the vehicle.

Classes IPC  ?

• G06T 11/00 - Génération d'images bidimensionnelles [2D]
• H04L 67/63 - Ordonnancement ou organisation du service des demandes d'application, p.ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises en acheminant une demande de service en fonction du contenu ou du contexte de la demande
• G06T 7/90 - Détermination de caractéristiques de couleur
• H04W 4/44 - Services spécialement adaptés à des environnements, à des situations ou à des fins spécifiques pour les véhicules, p.ex. communication véhicule-piétons pour la communication entre véhicules et infrastructures, p.ex. véhicule à nuage ou véhicule à domicile
• G01C 21/34 - Recherche d'itinéraire; Guidage en matière d'itinéraire
• G06T 11/60 - Edition de figures et de texte; Combinaison de figures ou de texte
• H04L 67/51 - Découverte ou gestion de ceux-ci, p.ex. protocole de localisation de service [SLP] ou services du Web
• G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
• G06F 40/221 - Analyse syntaxique de flux de langages de balisage
• G06F 3/04817 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p.ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comport utilisant des icônes

Abrégé

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for exchange and synchronization of status information of a vehicle. One of the methods includes obtaining, by a terminal, status information of the vehicle from equipment on the vehicle and connected to the terminal, sending, by the terminal, the status information to a server, and receiving, by the terminal and from the server, an updated status identifier associated with the terminal, wherein the updated status identifier is determined based on the status information.

Classes IPC  ?

• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
• G06Q 10/02 - Réservations, p.ex. pour billetterie, services ou manifestations
• G06Q 50/30 - Transport; Communications

Abrégé

A method and system for recognizing a certificate on the basis of a graph neural network. The method comprises: obtaining an image to be recognized (310); detecting content text comprised in the image to be recognized, and determining multiple bounding boxes (320); constructing a layout on the basis of the multiple bounding boxes (330), wherein the layout comprises a plurality of nodes and a plurality of edges, each node corresponds to a bounding box, and each edge correspond to the spatial position relationship between a bounding box and another bounding box; and processing the layout using a trained graph neural network model to determine field categories in the bounding boxes in the layout (340), and performing text recognition on key fields, so as to extract key information in the certificate.

Classes IPC  ?

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

Abrégé

A method may comprise obtaining a machine-learning output generated by a computer system running a trained machine-learning model; obtaining characteristics associated with the generation of the output, the characteristics comprising at least one of an energy term or a power term; determining a precision term for the system based on a comparison of the output with a reference; and determining an overall score of the system based on the precision term and the characteristics.

Classes IPC  ?

• G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
• G06N 20/00 - Apprentissage automatique
• G06F 40/58 - Utilisation de traduction automatisée, p.ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel

Abrégé

A method and system for reminding a user. The method comprises: acquiring positioning information of a user terminal, wherein the positioning information reflects information of the current road section of a vehicle in which a user is located (310); when the current road section is a restricted parking road section, determining a stay duration of the vehicle on the current road section (320); determining whether the stay duration is greater than a first safe stay duration (330); and in response to the stay duration being greater than the first safe stay duration, sending first-level reminder information to the user terminal (340).

Classes IPC  ?

• G06F 16/29 - Bases de données d’informations géographiques