One-Shot Learning-Based SAR Ship Classification Using New Hybrid Siamese Network
Author:
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology
Link
http://xplorestaging.ieee.org/ielx7/8859/9651998/09512781.pdf?arnumber=9512781
Cited by 15 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. SEFRNet: An SAR Ship Target Detection Network With Effective Feature Representation;IEEE Sensors Journal;2024-03-15
2. Attention-Guided Convolution Neural Network Assisted With Handcrafted Features for Ship Classification in Low-Resolution Sentinel-1 SAR Image Data;IEEE Access;2024
3. Feature Generation-Aided Zero-Shot Fast SAR Target Recognition With Semantic Attributes;IEEE Geoscience and Remote Sensing Letters;2024
4. A Unified Multiple Proxy Deep Metric Learning Framework Embedded With Distribution Optimization for Fine-Grained Ship Classification in Remote Sensing Images;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024
5. Improving Out-of-Distribution Generalization in SAR Image Scene Classification with Limited Training Samples;Remote Sensing;2023-12-17
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