The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jun. 20, 2023

Filed:

Nov. 16, 2017
Applicants:

Samsung Electronics Co., Ltd., Suwon-si, KR;

Korea Advanced Institute of Science and Technology, Daejeon, KR;

Inventors:

Kyung-su Kim, Seoul, KR;

Yukyung Choi, Daejeon, KR;

Sung-jin Kim, Yongin-si, KR;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2023.01); G06N 3/04 (2023.01); G06T 7/00 (2017.01); G06T 7/55 (2017.01); G06T 1/00 (2006.01); G06V 20/00 (2022.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G06N 3/04 (2013.01); G06T 1/00 (2013.01); G06T 7/0006 (2013.01); G06T 7/55 (2017.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06V 20/00 (2022.01);
Abstract

Provided are an AI system for simulating functions such as recognition, determination, and so forth of human brains by using a mechanical learning algorithm like deep learning, or the like, and an application thereof. In particular, according to the AI system and the application thereof, a neural network training method includes obtaining a plurality of first images belonging to a particular category and a plurality of second images for which a category is not specified, training a neural network model for category recognition, based on the plurality of first images belonging to the particular category, recognizing at least one second image corresponding to the particular category among the plurality of second images, by using the trained neural network model, and modifying and refining the trained neural network model based on the recognized at least one second image.


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