公开(公告)号：US20170300700A1

公开(公告)日：2017-10-19

申请号：US15510519

申请日：2015-08-11

Applicant: Samsung Electronics Co., Ltd.

Inventor： Suxia LI ,  Shu Tan ,  Yuanyou LI ,  Chao YU ,  Chonghua MEI ,  Fan LI ,  Feng SONG ,  Hong YANG ,  Jian CAO ,  Jingting GAO ,  Shifei GE ,  Yuan ZHONG

IPC: G06F21/62 ,  G06K9/00 ,  G06F21/32 ,  G06F3/0488 ,  G06F21/84 ,  G06F3/0481

CPC classification number: G06F21/629 ,  G06F3/04817 ,  G06F3/0488 ,  G06F3/04883 ,  G06F21/32 ,  G06F21/84 ,  G06F2203/0338 ,  G06K9/00087 ,  G06K9/00926

Abstract: Provided are a method of controlling a lock status of an application and an electronic device supporting the method. The method includes receiving a first touch input on a first icon displayed on a screen, detecting a first duration for which the first touch input is maintained, and setting a lock status of an application corresponding to the first icon in response to the first duration being greater than or equal to a first threshold period.

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.

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.