公开(公告)号：US12038968B2

公开(公告)日：2024-07-16

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

CPC classification number: 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.

公开(公告)号：US11178275B2

公开(公告)日：2021-11-16

申请号：US16739662

申请日：2020-01-10

Applicant: Samsung Electronics Co., Ltd.

Inventor： Chengjun Wang ,  Xin Liu ,  Feng Tang ,  Suxia Li ,  Bo Peng ,  Lei Wan

IPC: H04M3/22 ,  H04M3/42 ,  G06N3/08

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.