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:
Oct. 01, 2024

Filed:

Apr. 01, 2024
Applicant:

Shanghai Jiao Tong University, Shanghai, CN;

Inventors:

Wenrui Dai, Shanghai, CN;

Yaoming Wang, Shanghai, CN;

Yuchen Liu, Shanghai, CN;

Chenglin Li, Shanghai, CN;

Junni Zou, Shanghai, CN;

Hongkai Xiong, Shanghai, CN;

Assignee:
Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/00 (2022.01); G06V 10/764 (2022.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G06V 20/70 (2022.01);
U.S. Cl.
CPC ...
G06V 10/765 (2022.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G06V 20/70 (2022.01);
Abstract

The present disclosure provides an image classification method for maximizing mutual information, device, medium and system, the method including: acquiring a training image; maximizing the mutual information between the training image and a neural network architecture, and automatically determining the network architecture and parameter of the neural network; and processing image data to be classified using the obtained neural network to obtain an image classification result. According to the present disclosure, the network architecture and parameter of the neutral network are automatically designed and determined by maximizing the mutual information based on given image data without burdensome manual design and saving human and computational resource consumption. The present disclosure can automatically design and obtain a neural network-based image classification method in a very short time, and at the same time can achieve higher image classification accuracy.


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