公开(公告)号：US20200013371A1

公开(公告)日：2020-01-09

申请号：US16573487

申请日：2019-09-17

Applicant: LG Electronics Inc.

Inventor： Jin Seok YANG ,  Min Jae KIM

IPC: G09G5/02 ,  G06T7/00 ,  G06K9/62 ,  G06N3/08 ,  G06N3/04

Abstract: A screen adjusting system includes a data collector for collecting data related to a full screen generated by resizing the full screen or cropping a portion of the full screen on the display, a screen classifier for applying the collected data to a learned AI model for classifying the image quality or the genre of the full screen, or whether the full screen is a text/an image, a screen adjuster for adjusting the screen of the display based on the image quality of the full screen, the genre of the content of the full screen, or whether the full screen is a text/an image, which have been classified, and a communicator for communicating with the server. According to the present disclosure, it is possible to control the display by using the AI, the AI based screen recognition technology, and the 5G network without manually adjusting the display screen.

公开(公告)号：US20210133424A1

公开(公告)日：2021-05-06

申请号：US16743456

申请日：2020-01-15

Applicant: LG Electronics Inc.

Inventor： Young Ho SOHN ,  Young Yeon SEO ,  Chang Jun YEO ,  Jin Seok YANG

IPC: G06K9/00 ,  G06F21/32 ,  G06N3/08 ,  G06K9/62 ,  H04M1/725 ,  G06Q20/40

Abstract: A method for biometrics spoofing detection according to an embodiment of the present disclosure includes receiving a biometric authentication request from an application, acquiring biometrics at a sensor, and applying a machine learning-based anti-spoofing scheme to the biometrics based on an authentication purpose of the biometrics. The anti-spoofing scheme for biometrics of the present disclosure may include a deep neural network generated by machine learning, and may be used in an Internet of Things environment using a 5G network.

公开(公告)号：US20200042687A1

公开(公告)日：2020-02-06

申请号：US16599894

申请日：2019-10-11

Applicant: LG ELECTRONICS INC.

Inventor： Won Kwang CHOI ,  Jin Seok YANG

IPC: G06F21/32 ,  G06N3/08 ,  G06F3/0346 ,  G06F3/0488

Abstract: A method for authenticating a user of a portable computing device according to an embodiment of the present disclosure includes identifying an application executed on the portable computing device, collecting touch data on the portable computing device and/or motion data of the portable computing device during execution of the application, and determining whether the pattern of the collected touch data and/or motion data corresponds to a usage pattern profile associated with the identified application. Whether the pattern of the touch data and/or the motion data corresponds to the usage pattern profile is determined in a Machine Learning or Deep Learning manner using an artificial neural network trained to output the corresponding degree between the usage pattern profile and the input data. According to the present disclosure, it is possible to authenticate the user in real time without disturbing the user during the use of the portable computing device.