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:
Sep. 23, 2025

Filed:

Sep. 17, 2021
Applicant:

Zhejiang University, Zhejiang, CN;

Inventors:

Jianwei Yin, Hangzhou, CN;

Yuxiang Cai, Hangzhou, CN;

Yingchun Yang, Hangzhou, CN;

Shuiguang Deng, Hangzhou, CN;

Ying Li, Hangzhou, CN;

Assignee:

ZHEJIANG UNIVERSITY, Hangzhou, CN;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/12 (2017.01); G06T 11/60 (2006.01);
U.S. Cl.
CPC ...
G06T 7/12 (2017.01); G06T 11/60 (2013.01);
Abstract

The present invention discloses a semantic segmentation method for cross-satellite remote sensing images based on unsupervised bidirectional domain adaptation and fusion. The method includes training of bidirectional source-target domain image translation models, selection of bidirectional generators in the image translation models, bidirectional translation of source-target domain images, training of source and target domain semantic segmentation models, and generation and fusion of source and target domain segmentation probabilities. According to the present invention, by utilizing source-target and target-source bidirectional domain adaptation, the source and target domain segmentation probabilities are fused, which improves the accuracy and robustness of a semantic segmentation model for the cross-satellite remote sensing images; and further, through the bidirectional semantic consistency loss and the selection of the parameters of the generators, the influence due to the instability problem of the generators in the bidirectional image translation models is avoided.


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