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. 24, 2024

Filed:

Sep. 16, 2021
Applicant:

Beijing Boe Technology Development Co., Ltd., Beijing, CN;

Inventors:

Libo Zhang, Beijing, CN;

Yuanyuan Lu, Beijing, CN;

Wangqiang He, Beijing, CN;

Dong Chai, Beijing, CN;

Hong Wang, Beijing, CN;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06T 11/00 (2006.01); G06F 18/10 (2023.01); G06F 18/21 (2023.01); G06F 18/214 (2023.01); G06F 18/24 (2023.01); G06T 7/00 (2017.01);
U.S. Cl.
CPC ...
G06F 18/217 (2023.01); G06F 18/10 (2023.01); G06F 18/214 (2023.01); G06F 18/24 (2023.01); G06T 7/0004 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01);
Abstract

The present disclosure relates to an image data classification method, device and system, and relates to the field of computer technology. The method includes: inputting test image data into a neural network model trained by using an original training sample set for classification, and determining an image type to which the test image data belongs and a membership probability of the image data belonging to the image type; establishing an easy-to-classify data set, according to test image data with a membership probability greater than a first threshold; adding test image data in the easy-to-classify data set that has a classification accuracy rate less than or equal to a second threshold and a correct classification result to the original training sample set to generate an augmented training sample set; and using the augmented training sample set to train the neural network model so as to determine an image class.


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