A Complex-Valued and Loss Optimized BiSeNet for PolSAR Image Semantic Segmentation-Reference-Cited by-同舟云学术

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A Complex-Valued and Loss Optimized BiSeNet for PolSAR Image Semantic Segmentation

Published:2023-12-04 Issue: Volume: Page:1-4
ISSN:
Container-title:2023 4th China International SAR Symposium (CISS)
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Author:

Xu Ruiqi¹,Zhao Xiaopeng²,Zuo Guanzhong³,Guo Rui²,Wang Hui⁴,Zhang Shuangxi¹

Affiliation:

1. School of Electronics and Information, Northwestern Polytechnical University,Xi'an,China

2. School of Automation, Northwestern Polytechnical University,Xi'an,China

3. School of Automation, Beijing Institute of Technology,Beijing,China

4. Shanghai Institute of Satelite Engineering,Shanghai,China

Funder

National Natural Science Foundation of China

Aeronautical Science Foundation of China

Shanghai Aerospace Science and Technology Innovation Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10379850/10379861/10379930.pdf?arnumber=10379930

Reference8 articles.

1. Statistical Scattering Component-Based Subspace Alignment for Unsupervised Cross-Domain PolSAR Image Classification

2. Classification of PolSAR Images Based on SVM with Self-Paced Learning Optimization

3. Decomposition-Feature-Iterative-Clustering-Based Superpixel Segmentation for PolSAR Image Classification

4. PolSAR Image Classification Using Polarimetric-Feature-Driven Deep Convolutional Neural Network

5. Attention-Based Multiscale Sequential Network for PolSAR Image Classification

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