公开(公告)号：US11899884B2

公开(公告)日：2024-02-13

申请号：US17965373

申请日：2022-10-13

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Hyunbin Park ,  Junhyuk Lee ,  Jin Choi

IPC: G06F1/03 ,  G06F3/16 ,  G06V40/50 ,  G06V40/13 ,  G06V40/60 ,  G06F3/0488 ,  G06F3/044 ,  G06F21/32 ,  G06V40/12 ,  G06F3/041

CPC classification number: G06F3/04186 ,  G06F3/0446 ,  G06F3/0488 ,  G06F3/165 ,  G06F21/32 ,  G06V40/1318 ,  G06V40/1365 ,  G06V40/50 ,  G06V40/67 ,  G06F2203/04105

Abstract: An example electronic device may include a fingerprint sensor, a touch sensor, a memory, and a processor. The processor may be configured to determine whether a touch input is generated, determine whether the generated touch input continues for a given time or more, generate first data by accumulating the touch input generated based on the touch input continuing for the given time or more, determine whether an inputted fingerprint corresponds to a registered fingerprint of a registered user, analyze the first data using a first AI model based on the inputted fingerprint corresponding to the registered fingerprint, analyze the first data using a second AI model based on the inputted fingerprint not corresponding to the registered fingerprint, identify a form of the touch input based on the first data, and perform a function and/or execute a user interface corresponding to the identified form of the touch input.

公开(公告)号：US11676580B2

公开(公告)日：2023-06-13

申请号：US17245751

申请日：2021-04-30

Applicant: Samsung Electronics Co., Ltd.

Inventor： Hyunbin Park ,  Jin Choi

IPC: G10L15/16 ,  G10L25/51 ,  G10L25/30 ,  G06F9/50 ,  G06F7/544 ,  G06F7/523 ,  G06F7/50 ,  G10L15/08

CPC classification number: G10L15/16 ,  G06F7/50 ,  G06F7/523 ,  G06F7/5443 ,  G06F9/5027 ,  G10L25/30 ,  G10L25/51 ,  G10L2015/088

Abstract: An electronic device is provided. The electronic device includes a microphone, and at least one processor operatively connected to the microphone, wherein the at least one processor may include a buffer memory configured to store a first feature vector for a first voice signal obtained from the microphone as an inverse value, and an operation circuit configured to perform a norm operation for a first feature vector and a second feature vector, based on the second feature vector, based on a second voice signal streamed from the microphone and an inverse value of the first feature vector stored in the buffer memory, or calculate a similarity between the first feature vector and the second feature vector. In addition, various embodiments identified through the specification are possible.

公开(公告)号：US12254151B2

公开(公告)日：2025-03-18

申请号：US18507634

申请日：2023-11-13

Applicant: Samsung Electronics Co., Ltd.

Inventor： Junhyuk Lee ,  Hyunbin Park ,  Seungjin Yang ,  Jin Choi

IPC: G06F3/041 ,  G06F3/0488

Abstract: An electronic device is provided. The electronic device includes a touch sensor, a processor, and a memory. The processor may determine a touch input from a user as at least one of a force-touch input or a long-touch input, based on received touch data, determine whether a result of determining the touch data matches an intention of the user, store data that does not match the intention of the user as a result of determination among the touch data in the memory, and determine a type of an artificial intelligence (AI)-based pre-learning model to be used in the electronic device, based on touch input accuracy and the data that does not match the intention of the user.

公开(公告)号：US11874995B2

公开(公告)日：2024-01-16

申请号：US17899138

申请日：2022-08-30

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Junhyuk Lee ,  Hyunbin Park ,  Seungjin Yang ,  Jin Choi

IPC: G06F3/041 ,  G06N3/045

CPC classification number: G06F3/0418 ,  G06N3/045

Abstract: According to various embodiments, an electronic device includes a memory storing deep learning models for determining a force touch, a touchscreen, and a processor configured to identify a touch input of a user through the touchscreen, receive touch pixel data for frames having a time difference based on the touch input, and identify whether the touch input is a force touch based on the touch pixel data. The processor is configured to identify whether the touch input is the force touch using a first determination model among the deep learning models in response to identifying that the touch input is reinputted a designated first number of times or more within a designated time, and otherwise, identify whether the touch input is the force touch using a determination model having a lower computation load than the first determination model among the deep learning models.