MF-YOLO improves small-object detection at the cost of substantially greater computation, and introduces a stride-4 P2 prediction scale, applies Global-to-Local Spatial Aggregation independently to C2–C5 before neck fusion, and connects P2–P5 through a 64-channel Bidirectional Feature Pyramid Network (BiFPN).
Yu-Fei Wang, Ji-Ming Yang, Fang Liu et al.· Italian National Conference...· 0 citations
M-FSAD-KD is proposed, a full-link distillation framework whose neck-stage Fourier-gated alignment transfers low-frequency structural content while preserving target-edge high-frequency content; a joint spatial–channel attention mask, a shallow backbone adapter, and a response-level knowledge distillation (KD) term com...
Yu-Ming Tong, Kai-Na Xiong, Jun Liu et al.· Remote Sensing· 0 citations
A remote sensing image landslide segmentation network (VFM-MoME) jointly guided by a vision foundation model and a mixture of Mamba experts is proposed, mitigating the issue of insufficient generalized features in specific landslide study areas and enhancing the model’s ability to handle ambiguous features.
Jun Liu, Chengqiang Zhao, Yuan-zhen Ju et al.· Remote Sensing· 0 citations
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