Information Reconstruction-Based Polarimetric Covariance Matrix for PolSAR Ship Detection

Author:

Zhang Tao1ORCID,Quan Sinong2ORCID,Wang Wei2ORCID,Guo Weiwei3ORCID,Zhang Zenghui1ORCID,Yu Wenxian1ORCID

Affiliation:

1. Shanghai Key Laboratory of Intelligent Sensing and Recognition, School of Sensing Science and Engineering, Shanghai Jiao Tong University, Shanghai, China

2. College of Electronic Science and Technology, National University of Defense Technology, Changsha, China

3. Center for Digital Innovation, Tongji University, Shanghai, China

Funder

National Natural Science Foundation of China

Double First-Class Construction Foundation

ESA-Most China Dragon 5 Programme

China Postdoctoral Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Complex-Valued 2D-3D Hybrid Convolutional Neural Network with Attention Mechanism for PolSAR Image Classification;Remote Sensing;2024-08-09

2. MSE-Net: A novel master–slave encoding network for remote sensing scene classification;Engineering Applications of Artificial Intelligence;2024-06

3. A Lightweight Theory-Driven Network and Its Validation on Public Fully Polarized Ship Detection Dataset;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

4. Evaluating the Robustness of Polarimetric Features: A Case Study of PolSAR Ship Detection;IEEE Geoscience and Remote Sensing Letters;2024

5. Dual Attention-Based Difference Amplification Shrinkage Network for Unsupervised Change Detection in PolSAR Images;2023 6th International Conference on Information Communication and Signal Processing (ICICSP);2023-09-23

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