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:
Dec. 05, 2023

Filed:

Sep. 30, 2020
Applicants:

Huawei Technologies Co., Ltd., Shenzhen, CN;

Institute of Automation, Chinese Academy of Sciences, Beijing, CN;

Inventors:

Bailan Feng, Beijing, CN;

Chunfeng Yao, Beijing, CN;

Kaiqi Huang, Beijing, CN;

Zhang Zhang, Beijing, CN;

Xiaotang Chen, Beijing, CN;

Houjing Huang, Beijing, CN;

Dangwei Li, Beijing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2023.01); G06N 20/00 (2019.01); G06T 3/40 (2006.01); G06F 18/213 (2023.01); G06V 10/774 (2022.01); G06V 20/52 (2022.01); G06N 3/084 (2023.01); G06N 5/046 (2023.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G06F 18/213 (2023.01); G06N 20/00 (2019.01); G06T 3/4007 (2013.01); G06V 10/774 (2022.01); G06V 20/52 (2022.01); G06N 3/084 (2013.01); G06N 5/046 (2013.01);
Abstract

An image processing method, a related device, and a computer storage medium are provided. The method includes: obtaining a feature intensity image corresponding to a training image, where an intensity value of a pixel in the feature intensity image is used to indicate importance of the pixel for recognizing the training image, and resolution of the training image is the same as resolution of the feature intensity image; and occluding, based on the feature intensity image, a to-be-occluded region in the training image by using a preset window, to obtain a new image, where the to-be-occluded region includes a to-be-occluded pixel, and the new image is used to update an image recognition model. According to the embodiments of the present application, a prior-art problem that a model has low accuracy and relatively poor generalization performance because of limited training data can be resolved.


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