Rendering-Inspired Cross-Source Feature Disentanglement for Domain Adaptation- Based SAR Ship Classification-Reference-Cited by-同舟云学术

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Rendering-Inspired Cross-Source Feature Disentanglement for Domain Adaptation- Based SAR Ship Classification

Published:2024 Issue: Volume:21 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Zhang Haonan¹,Lv Yafei²^ORCID,Zhang Jianting²,Wu Qian³^ORCID,Wen Zaidao¹^ORCID

Affiliation:

1. Key Laboratory of Information Fusion Technology of the Ministry of Education, Northwestern Polytechnical University, Xi’an, Shaanxi, China

2. Naval Research Institute of PLA, Beijing, China

3. Institute of Information and Navigation, Air Force Engineering University, Xi’an, Shaanxi, China

Funder

National Natural Science Foundation of China

Natural Science Basic Research Plan in Shaanxi Province of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/8859/10365397/10497597.pdf?arnumber=10497597

Reference30 articles.

1. A tutorial on synthetic aperture radar

2. Ship Classification in TerraSAR-X Images With Feature Space Based Sparse Representation

3. Ship Classification Based on Superstructure Scattering Features in SAR Images

4. Ship Classification in SAR Image by Joint Feature and Classifier Selection

5. Ship-Iceberg Classification in SAR and Multispectral Satellite Images with Neural Networks

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