Balance Scene Learning Mechanism for Offshore and Inshore Ship Detection in SAR Images
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Abstract (arXiv)
Huge imbalance of different scenes' sample numbers seriously reduces Synthetic Aperture Radar (SAR) ship detection accuracy. Thus, to solve this problem, this letter proposes a Balance Scene Learning Mechanism (BSLM) for offshore and inshore ship detection in SAR images.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 21 Jul 2020.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 0; 2024: 0; 2025: 1.
4 papers.
- 2022A Mask Attention Interaction and Scale Enhancement Network for SAR Ship Instance Segmentationcited by 7
- 2021Semantic Attention and Scale Complementary Network for Instance Segmentation in Remote Sensing Imagescited by 5
- 2022A Dual-Polarization Information Guided Network for SAR Ship Classificationcited by 2
- 2025Scene-aware SAR ship detection guided by unsupervised sea-land segmentationcited by 0
- 2025Scene-aware SAR ship detection guided by unsupervised sea-land segmentation15 Jun 2025
- 2022A Dual-Polarization Information Guided Network for SAR Ship Classification11 Jul 2022
- 2022A Mask Attention Interaction and Scale Enhancement Network for SAR Ship Instance Segmentation8 Jul 2022
- 2021Semantic Attention and Scale Complementary Network for Instance Segmentation in Remote Sensing Images25 Jul 2021