US 12,254,151 B2
Electronic device and learning model determination method for learning of electronic device
Junhyuk Lee, Suwon-si (KR); Hyunbin Park, Suwon-si (KR); Seungjin Yang, Suwon-si (KR); and Jin Choi, Suwon-si (KR)
Assigned to Samsung Electronics Co., Ltd., Suwon-si (KR)
Filed by Samsung Electronics Co., Ltd., Suwon-si (KR)
Filed on Nov. 13, 2023, as Appl. No. 18/507,634.
Application 18/507,634 is a continuation of application No. PCT/KR2023/012268, filed on Aug. 18, 2023.
Claims priority of application No. 10-2022-0103967 (KR), filed on Aug. 19, 2022; and application No. 10-2022-0113689 (KR), filed on Sep. 7, 2022.
Prior Publication US 2024/0077970 A1, Mar. 7, 2024
Int. Cl. G06F 3/041 (2006.01); G06F 3/0488 (2022.01)
CPC G06F 3/0416 (2013.01) [G06F 3/0488 (2013.01)] 20 Claims
OG exemplary drawing
 
1. An electronic device comprising:
a touch sensor;
a processor configured to be operatively connected to the touch sensor; and
a memory,
wherein the processor is configured to, based on execution of instructions stored in the memory:
receive touch data corresponding to a touch input from a user by using the touch sensor,
determine the touch input from the user as at least one of a force-touch input or a long-touch input, based on the 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 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.