Joint Self-Training and Rebalanced Consistency Learning for Semi-Supervised Change Detection
Author:
Affiliation:
1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
2. School of Remote Sensing and Information Engineering and the Luojia Laboratory, Wuhan University, Wuhan, China
Funder
National Natural Science Foundation of China
Special Fund of Hubei Luojia Laboratory
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/10006360/10248040.pdf?arnumber=10248040
Reference66 articles.
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3. SemiSANet: A Semi-Supervised High-Resolution Remote Sensing Image Change Detection Model Using Siamese Networks with Graph Attention
4. FSANet: Feature-and-Spatial-Aligned Network for Tiny Object Detection in Remote Sensing Images
5. General E(2)-equivariant steerable CNNs;weiler;Proc Adv Neural Inf Process Syst,2019
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