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. 27, 2023

Filed:

May. 13, 2020
Applicant:

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

Inventor:

Yosub Park, Suwon-si, KR;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2022.01); G06T 7/00 (2017.01); G06N 20/00 (2019.01); H04N 5/232 (2006.01); G06N 3/08 (2006.01); G06V 40/10 (2022.01); G06V 20/58 (2022.01); G06F 18/22 (2023.01); G06F 18/2113 (2023.01); H04N 23/661 (2023.01); G06V 10/74 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G06V 40/10 (2022.01); G06F 18/2113 (2023.01); G06F 18/22 (2023.01); G06N 3/08 (2013.01); G06N 20/00 (2019.01); G06T 7/0002 (2013.01); G06V 10/761 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 20/58 (2022.01); H04N 23/661 (2023.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30261 (2013.01);
Abstract

An electronic device may include a processor configured to: obtain a plurality of images, the plurality of images including a first image captured by a first camera or image sensor, and a second image captured by a second camera or image sensor. The processor may further be configured to: determine whether a first object and a second object respectively included in the first image and the second image are a same object, and based on determining that the first object and the second object are the same object, train a neural network data recognition model to recognize the first object and the second object as the same object in both the first image and the second image by using the first image and the second image as training data of the neural network data recognition model.


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