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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.

Patent No.:

US 11899710 B1

PDFFull Text
Date of Patent:
Feb. 13, 2024

Filed:

Jun. 28, 2021

Image recognition method, electronic device and storage medium

Applicant:

Beijing Baidu Netcom Science and Technology Co., Ltd, Beijing, CN;

Inventor:

Min Yang, Beijing, CN;

Assignee:

Beijing Baidu Netcom Science and Technology Co., Ltd., Beijing, CN;

Attorney:

Banner & Witcoff, Ltd.

Primary Examiner:

Nancy Bitar

Assistant Examiner:

Dustin Bilodeau

Int. Cl.
CPC ...
G06V 10/82 (2022.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01); G06F 18/20 (2023.01); G06F 16/55 (2019.01); G06F 18/25 (2023.01); G06F 18/24 (2023.01); G06F 18/214 (2023.01); G06F 18/21 (2023.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 10/80 (2022.01); G06V 10/44 (2022.01); G06V 20/00 (2022.01);
U.S. Cl.
CPC ...
G06F 16/55 (2019.01); G06F 18/214 (2023.01); G06F 18/217 (2023.01); G06F 18/24 (2023.01); G06F 18/253 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06V 10/454 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 10/809 (2022.01); G06V 10/82 (2022.01); G06V 20/00 (2022.01);
Abstract

An image recognition method, electronic device, and storage medium are provided and relate to the fields of artificial intelligence, computer vision, deep learning, image processing, and the like. The method includes: performing joint training on a first sub-network configured for recognition processing and a second sub-network configured for retrieval processing in a classification network by adopting an identical set of training data to obtain a trained target classification network, wherein, the first sub-network and the second sub-network are twin networks that are consistent in network structures and share a set of weights; and inputting image data to be recognized into the target classification network to obtain a recognition result. By adopting the method, the accuracy of the image recognition may be improved.

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