A CA-Based Weighted Clustering Adversarial Network for Unsupervised Domain Adaptation PolSAR Image Classification-Reference-Cited by-同舟云学术

A CA-Based Weighted Clustering Adversarial Network for Unsupervised Domain Adaptation PolSAR Image Classification

Published:2023 Issue: Volume:20 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Hua Wenqiang¹^ORCID,Liu Lin¹^ORCID,Sun Nan¹^ORCID,Jin Xiaomin¹^ORCID

Affiliation:

1. Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing and the Xi’an Key Laboratory of Big Data and Intelligent Computing, School of Computer Science and Technology, Xi’an University of Posts and Telecommunications, Xi’an, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

http://xplorestaging.ieee.org/ielx7/8859/10034981/10305205.pdf?arnumber=10305205

Reference14 articles.

1. Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation

2. Maximum Classifier Discrepancy for Unsupervised Domain Adaptation

3. Cross-Domain Gradient Discrepancy Minimization for Unsupervised Domain Adaptation

4. Bi-classifier determinacy maximization for unsupervised domain adaptation;li;Proc IEEE/CVF Conf Comput Vis Pattern Recognit (CVPR),2020

5. Coordinate Attention for Efficient Mobile Network Design

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