# Balance Scene Learning Mechanism for Offshore and Inshore Ship Detection in SAR Images

arXiv: https://arxiv.org/abs/2007.10714 · HTML: https://mlsanity.com/paper/2007.10714/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Jul 2020.

## Built on by (most cited first, 4 of 4)

- [A Mask Attention Interaction and Scale Enhancement Network for SAR Ship Instance Segmentation](https://mlsanity.com/paper/2207.03912/) (2022)
- [Semantic Attention and Scale Complementary Network for Instance Segmentation in Remote Sensing Images](https://mlsanity.com/paper/2107.11758/) (2021)
- [A Dual-Polarization Information Guided Network for SAR Ship Classification](https://mlsanity.com/paper/2207.04639/) (2022)
- [Scene-aware SAR ship detection guided by unsupervised sea-land segmentation](https://mlsanity.com/paper/2506.12775/) (2025)

## 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.