SARES-DEIM achieves 76.4% mAP50:95 and 93.8% mAP50 on HRSID by routing SAR features through sparse frequency and wavelet experts plus a high-resolution preservation neck, outperforming prior YOLO and SAR detectors.
Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection
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SFFNet uses multi-scale dynamic dual-domain coupling and a synergistic feature pyramid network to reach 36.8 AP on VisDrone and 20.6 AP on UAVDT for UAV object detection.
STAR-IOD applies scale-decoupled topology alignment and K-Means-based pseudo-label refinement to reduce catastrophic forgetting in remote sensing incremental object detection, reporting 1.7% and 2.1% mAP gains on new DIOR-IOD and DOTA-IOD datasets.
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SFFNet: Synergistic Feature Fusion Network With Dual-Domain Edge Enhancement for UAV Image Object Detection
SFFNet uses multi-scale dynamic dual-domain coupling and a synergistic feature pyramid network to reach 36.8 AP on VisDrone and 20.6 AP on UAVDT for UAV object detection.