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公开(公告)号：US20230073235A1
公开(公告)日：2023-03-09
申请号：US17939665
申请日：2022-09-07
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Chengjun WANG
Abstract: The present disclosure discloses a method for federated learning, including: requesting, by a target application, a user to provide a federated learning data access right to access privacy data; calling, by the target application, a unified federated learning service (UnifiedFED) application to perform horizontal federated learning, acquiring, by the UnifiedFED application, the privacy data isolated from the target application according to the federated learning data access right, receiving, by the UnifiedFED application, non-privacy data from the target application, and providing, by the UnifiedFED application, the privacy data and the non-privacy data to an artificial intelligence (AI) model for federated learning training.
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公开(公告)号：US20230050371A1
公开(公告)日：2023-02-16
申请号：US17887235
申请日：2022-08-12
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Chengjun WANG
IPC: G06F16/532 , G06F16/583 , G06F40/30
Abstract: The application discloses a method and device for personalized search of visual media. Semantic analysis is conducted on a visual media query text of a user to obtain visual semantic information, time information and/or location information. Semantic similarity matching is conducted on a result of the semantic analysis and attribute data of each visual medium within a specified search range to obtain a query similarity of the visual medium. The visual medium is an image or a video, and the attribute data include personalized visual semantic information, personalized time information and/or personalized location information. A corresponding visual media query result is generated based on the query similarity. By adopting the application, users are provided with visual media which is a result of a personalized.
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公开(公告)号：US20240119096A1
公开(公告)日：2024-04-11
申请号：US18217831
申请日：2023-07-03
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Chengjun WANG , Bo PENG , Jie CHEN
IPC: G06F16/953 , G06F16/951 , G06F21/31
CPC classification number: G06F16/953 , G06F16/951 , G06F21/31
Abstract: A meta-searching method, including determining a target metaverse for a current search using intent classification based on an inquiry text included in a searching request of a user; extracting a searching clue and a clue type; selecting a current search engine for performing the current search using the target metaverse and the clue type by prioritizing a search engine associated with the target metaverse; performing identity authentication using the user account information of the user in the target metaverse prior to the search based on determining that user account information is required to search for the searching clue for performing a search using the current search engine, and performing the search using the current search engine based on the searching clue; and providing the search results to the user.
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公开(公告)号：US20200228648A1
公开(公告)日：2020-07-16
申请号：US16739662
申请日：2020-01-10
Applicant: Samsung Electronics Co., Ltd.
Abstract: A method and an apparatus for detecting an abnormality of a caller are provided. The method includes at the beginning of a call, acquiring, by a terminal device, real voice/video data of a call object who needs abnormality detection and a corresponding pre-trained multi-stage neural network detection model, during the call, collecting, by the terminal device, call data according to a preset data collection policy, for each call object, inputting the currently collected call data and the real voice/video data of the call object into the model of the call object, and determining whether the call object is abnormal according to a detection result output by the model, in which the call data includes image data and/or voice data, and an identification manner adopted by the model includes face identification, voiceprint identification, limb movement identification, and/or lip language identification. By adopting the disclosure, the abnormality of the caller may be accurately detected, and the voice forgery and the video forgery mimicked by AI during a call may be accurately identified.
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