A Semisupervised Arbitrary-Oriented SAR Ship Detection Network Based on Interference Consistency Learning and Pseudolabel Calibration
Author:
Affiliation:
1. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China
2. Shenzhen International Graduate School, Tsinghua University, Shenzhen, China
Funder
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Atmospheric Science,Computers in Earth Sciences
Link
http://xplorestaging.ieee.org/ielx7/4609443/9973430/10147338.pdf?arnumber=10147338
Reference47 articles.
1. An Anchor-Free Detection Method for Ship Targets in High-Resolution SAR Images
2. Domain Adaptation for Semi-Supervised Ship Detection in SAR Images
3. SAR Target Classification with Limited Data via Data Driven Active Learning
4. A Semi-Supervised Sar Ship Detection Framework Via Label Propagation and Consistent Augmentation
5. SAR ship detection using sea-land segmentation-based convolutional neural network
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