A Novel Causal Inference-Guided Feature Enhancement Framework for PolSAR Image Classification-Reference-Cited by-同舟云学术

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A Novel Causal Inference-Guided Feature Enhancement Framework for PolSAR Image Classification

Published:2024 Issue: Volume:62 Page:1-16
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Dong Hongwei¹^ORCID,Si Lingyu¹,Qiang Wenwen¹^ORCID,Zhang Lamei²^ORCID,Yu Junzhi³^ORCID,Wu Yuquan¹,Zheng Changwen¹^ORCID,Sun Fuchun⁴^ORCID

Affiliation:

1. Science and Technology on Integrated Information System Laboratory, Institute of Software, Chinese Academy of Sciences, Beijing, China

2. Department of Information Engineering, Harbin Institute of Technology, Harbin, China

3. College of Engineering, Peking University, Beijing, China

4. Department of Computer Science and Technology, Tsinghua University, Beijing, China

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10360854.pdf?arnumber=10360854

Reference65 articles.

1. The legacy of the SIR-C/X-SAR radar system: 25 years on

2. Polarimetric decomposition of microwave-band freshwater ice SAR data: Review, analysis, and future directions

3. Environment Monitoring of Shanghai Nanhui Intertidal Zone With Dual-Polarimetric SAR Data Based on Deep Learning

4. Classification of SAR and PolSAR images using deep learning: a review

5. Backpropagation Applied to Handwritten Zip Code Recognition

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