SAR-Net: Multi-scale Direction-aware SAR Network via Global Information Fusion

arXiv:2312.16943v2 Announce Type: replace
Abstract: Deep learning has driven significant progress in object detection using Synthetic Aperture Radar (SAR) imagery. Existing methods, while achieving promising results, often struggle to effectively integrate local and global information, particularly direction-aware features. This paper proposes SAR-Net, a novel framework specifically designed for global fusion of direction-aware information in SAR object detection. SAR-Net leverages two key innovations: the Unity Compensation Mechanism (UCM) and the Direction-aware Attention Module (DAM). UCM facilitates the establishment of complementary relationships …

abstract arxiv cs.cv deep learning detection features framework fusion global information network novel object paper progress radar results scale struggle synthetic type via