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:
Aug. 08, 2023

Filed:

May. 21, 2020
Applicants:

Electronics and Telecommunications Research Institute, Daejeon, KR;

Information Technology University (Itu), Lahore, PK;

Inventors:

Yong Ju Cho, Daejeon, KR;

Jeong Il Seo, Daejeon, KR;

Rehan Hafiz, Lahore, PK;

Mohsen Ali, Lahore, PK;

Muhammad Faisal, Lahore, PK;

Aman Irshad, Lahore, PK;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2023.01); G06F 18/22 (2023.01); G06F 18/23 (2023.01); G06V 10/82 (2022.01); G06F 17/16 (2006.01); G06V 10/764 (2022.01); G06V 10/77 (2022.01); G06V 10/774 (2022.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G06F 17/16 (2013.01); G06F 18/22 (2023.01); G06F 18/23 (2023.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/7715 (2022.01); G06V 10/82 (2022.01);
Abstract

Disclosed herein is an image deep learning model training method. The method includes sampling a twin negative comprising a first negative sample and a second negative sample by selecting the first negative sample with a highest similarity out of an anchor sample and a positive sample constituting a matching pair in each class and by selecting the second negative sample with a highest similarity to the first negative sample, and training the samples to minimize a loss of a loss function in each class by utilizing the anchor sample, the positive sample, the first and second negative samples for each class. The first negative sample is selected in a different class from a class comprising the matching pair, and the second negative sample is selected in a different class from classes comprising the matching pair and the first negative sample.


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