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:
Nov. 18, 2025

Filed:

Aug. 15, 2022
Applicants:

Beijing Baidu Netcom Science Technology Co., Ltd., Beijing, CN;

State Key Laboratory of Internet of Things for Smart City (University of Macau), Macau S.A.R., CN;

Inventors:

Kafeng Wang, Beijing, CN;

Chengzhong Xu, Macau S.A.R., CN;

Haoyi Xiong, Beijing, CN;

Xingjian Li, Beijing, CN;

Dejing Dou, Beijing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/098 (2023.01); G06N 3/0985 (2023.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/778 (2022.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G06V 10/774 (2022.01); G06N 3/0985 (2023.01); G06V 10/764 (2022.01); G06V 10/778 (2022.01); G06V 10/82 (2022.01);
Abstract

A method and an apparatus for training a classification model and data classification includes: obtaining a sample set and a pre-trained classification model, wherein the classification model includes at least two convolutional layers, each convolutional layer is connected to a classification layer through a fully connected layer; inputting the sample set into the classification model, and obtaining a prediction result output by each classification layer, wherein the prediction result includes a prediction probability of a class to which each sample belongs; calculating a probability threshold of each classification layer based on the prediction result output by each classification layer; setting a prediction stopping condition for the classification mode according to the probability threshold of each classification layer.


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