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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 12450873 B1

PDFFull Text
Date of Patent:
Oct. 21, 2025

Filed:

Dec. 08, 2022

Data classification and recognition method and apparatus, device, and medium

Applicant:

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

Inventors:

Dong Wei, Shenzhen, CN;

Jinghan Sun, Shenzhen, CN;

Kai Ma, Shenzhen, CN;

Liansheng Wang, Shenzhen, CN;

Yefeng Zheng, Shenzhen, CN;

Assignee:

TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED, Shenzhen, CN;

Attorney:

Anova Law Group, PLLC

Primary Examiner:

Henok Shiferaw

Assistant Examiner:

Dennis undefined Rosario

Int. Cl.
CPC ...
G06V 10/764 (2022.01); G06F 18/213 (2023.01); G06F 18/241 (2023.01); G06F 18/25 (2023.01); G06N 3/088 (2023.01); G06N 3/0895 (2023.01); G06N 3/09 (2023.01); G06N 20/00 (2019.01); G06N 20/20 (2019.01); G06V 10/40 (2022.01); G06V 10/70 (2022.01); G06V 10/77 (2022.01); G06V 10/774 (2022.01); G06V 10/80 (2022.01); G06V 10/94 (2022.01); G06V 30/18 (2022.01); G06V 30/19 (2022.01); A61B 5/00 (2006.01); G06F 18/21 (2023.01); G06F 18/214 (2023.01); G06T 5/60 (2024.01); G06V 10/778 (2022.01); G10L 15/02 (2006.01); G10L 15/06 (2013.01); G10L 15/16 (2006.01); G10L 25/30 (2013.01);
U.S. Cl.
CPC ...
G06V 10/764 (2022.01); G06F 18/213 (2023.01); G06F 18/241 (2023.01); G06F 18/25 (2023.01); G06N 3/088 (2013.01); G06N 3/0895 (2023.01); G06N 3/09 (2023.01); G06N 20/00 (2019.01); G06N 20/20 (2019.01); G06V 10/40 (2022.01); G06V 10/70 (2022.01); G06V 10/7715 (2022.01); G06V 10/7753 (2022.01); G06V 10/803 (2022.01); G06V 10/806 (2022.01); G06V 10/809 (2022.01); G06V 10/95 (2022.01); G06V 30/18 (2022.01); G06V 30/19173 (2022.01); A61B 5/7264 (2013.01); A61B 5/7267 (2013.01); G06F 18/2155 (2023.01); G06F 18/2178 (2023.01); G06T 5/60 (2024.01); G06T 2207/20081 (2013.01); G06V 10/7784 (2022.01); G06V 10/7788 (2022.01); G10L 15/02 (2013.01); G10L 15/063 (2013.01); G10L 15/16 (2013.01); G10L 25/30 (2013.01);
Abstract

A data classification and recognition method includes: obtaining a first data set and a second data set, the second data set including second data, samples in the second data being labeled; performing training using first data in an unsupervised training mode and using the second data in a supervised training mode to obtain a first classification model; obtaining a second classification model; performing distillation training on a model parameter of the second classification model to obtain a data classification model; and performing class prediction on target data by using the data classification model.

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