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:
Jan. 26, 2021

Filed:

Nov. 29, 2018
Applicant:

Baidu Online Network Technology (Beijing) Co., Ltd., Beijing, CN;

Inventors:

Ming Sun, Beijing, CN;

Yuchen Yuan, Beijing, CN;

Feng Zhou, Beijing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2006.01); G06K 9/46 (2006.01); G06N 20/00 (2019.01); G06K 9/00 (2006.01);
U.S. Cl.
CPC ...
G06K 9/628 (2013.01); G06K 9/00684 (2013.01); G06K 9/46 (2013.01); G06K 9/4628 (2013.01); G06K 9/6215 (2013.01); G06K 9/6227 (2013.01); G06K 9/6228 (2013.01); G06K 9/6257 (2013.01); G06K 9/6274 (2013.01); G06N 20/00 (2019.01);
Abstract

The present disclosure provides a method and apparatus for training a fine-grained image recognition model, a device and a storage medium. The method comprises: obtaining images as training samples, and respectively obtaining a tag corresponding to each image, the tag including a class to which the image belongs; training according to the training samples and corresponding tags to obtain a fine-grained image recognition model, and performing constraint at a feature level from two dimensions, namely, the class and object parts, during the training, so that the fine-grained image recognition model learns key object parts in the images; upon performing the fine-grained image recognition, inputting a to-be-recognized image to the fine-grained image recognition model, so that the fine-grained image recognition model positions key object parts in the image, and completes fine-grained image classification according to the key object parts, and outputs a classification result. The solution of the present disclosure can be applied to save manpower costs and improve the model training efficiency.


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