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. 27, 2026

Filed:

Jun. 23, 2021
Applicant:

Tencent Technology (Shenzhen) Company Limited, Guangdong, CN;

Inventors:

Rong Bo Shen, Shenzhen, CN;

Ke Zhou, Shenzhen, CN;

Kuan Tian, Shenzhen, CN;

Ke Zhou Yan, Shenzhen, CN;

Cheng Jiang, Shenzhen, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2023.01); G06F 18/214 (2023.01); G06F 18/22 (2023.01); G06F 18/2431 (2023.01); G06N 3/045 (2023.01); G06V 10/74 (2022.01); G06V 10/764 (2022.01); G06V 10/77 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G06V 10/82 (2022.01); G06F 18/214 (2023.01); G06F 18/22 (2023.01); G06F 18/2431 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06V 10/761 (2022.01); G06V 10/764 (2022.01); G06V 10/7715 (2022.01); G06V 10/774 (2022.01);
Abstract

Provided are an artificial intelligence (AI)-based method and apparatus for training a classification task model, a device, and a storage medium, which relate to the field of machine learning (ML) technologies. The method includes: training an initial feature extractor by using a first dataset to obtain a feature extractor, the first dataset being a class imbalanced dataset; constructing a generative adversarial network, the generative adversarial network including the feature extractor and an initial feature generator; training the generative adversarial network by using second class samples to obtain a feature generator; constructing a classification task model, the classification task model including the feature generator and the feature extractor; and training the classification task model by using the first dataset, the feature generator being configured to augment the second class samples in a feature space in a training process of the classification task model.


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