Coarse-to-Fine Contrastive Self-Supervised Feature Learning for Land-Cover Classification in SAR Images With Limited Labeled Data-Reference-Cited by-同舟云学术

Coarse-to-Fine Contrastive Self-Supervised Feature Learning for Land-Cover Classification in SAR Images With Limited Labeled Data

Published:2022 Issue: Volume:31 Page:6502-6516
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Yang Meijuan¹^ORCID,Jiao Licheng²^ORCID,Liu Fang²^ORCID,Hou Biao²^ORCID,Yang Shuyuan²^ORCID,Zhang Yake²,Wang Jianlong³^ORCID

Affiliation:

1. School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China

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

3. School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, China

Funder

Fundamental Research Funds for the Central Universities

State Key Program of National Natural Science of China

Foundation for Innovative Research Groups of the National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9626658/09917366.pdf?arnumber=9917366

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