Self-Supervised Learning Guided by SAR Image Factors for Terrain Classification-Reference-Cited by-同舟云学术

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Self-Supervised Learning Guided by SAR Image Factors for Terrain Classification

Published:2024 Issue: Volume:62 Page:1-18
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Ren Zhongle¹^ORCID,Du Zhe¹,Liu Shaobo¹,Hou Biao¹^ORCID,Li Weibin¹^ORCID,Zhu Hao¹^ORCID,Ren Bo¹^ORCID,Jiao Licheng¹^ORCID

Affiliation:

1. Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, International Research Center for Intelligent Perception and Computation, Joint International Research Laboratory of Intelligent Perception and Computation, School of Artificial Intelligence, Xidian University, Xi’an, Shaanxi, China

Funder

National Natural Science Foundation of China

Higher Education Discipline Innovation Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10496083.pdf?arnumber=10496083

Reference51 articles.

1. Characterization of Land Cover Types in TerraSAR-X Images by Combined Analysis of Speckle Statistics and Intensity Information

2. Extraction of Sea Ice Cover by Sentinel-1 SAR Based on Support Vector Machine With Unsupervised Generation of Training Data

3. MDOAU-Net: A Lightweight and Robust Deep Learning Model for SAR Image Segmentation in Aquaculture Raft Monitoring

4. Study of SAR Image Texture Feature Extraction Based on GLCM in Guizhou Karst Mountainous Region

5. Deep Learning Meets SAR: Concepts, Models, Pitfalls, and Perspectives

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