A Fast Progressive Ship Detection Method for Very Large Full-Scene SAR Images
Author:
Affiliation:
1. Key Laboratory for Information Science of Electromagnetic Waves (MoE), Fudan University, Shanghai, China
Funder
National Natural Science Foundation of China
Natural Science Foundation of Shanghai
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/36/10354519/10453283.pdf?arnumber=10453283
Reference37 articles.
1. A review of recent advance of ship detection in single-channel SAR images
2. Texture discrimination in synthetic aperture radar imagery
3. Detection and Discrimination of Ship Targets in Complex Background From Spaceborne ALOS-2 SAR Images
4. FUSAR-Ship: building a high-resolution SAR-AIS matchup dataset of Gaofen-3 for ship detection and recognition
5. Deep Learning Meets SAR: Concepts, Models, Pitfalls, and Perspectives
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2. Ship Detection From Raw SAR Echoes Using Convolutional Neural Networks;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024
3. CroMoDa: Unsupervised Oriented SAR Ship Detection via Cross-Modality Distribution Alignment;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024
4. A Domain-Adaptive Few-Shot SAR Ship Detection Algorithm Driven by the Latent Similarity Between Optical and SAR Images;IEEE Transactions on Geoscience and Remote Sensing;2024
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