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HDMamba-YOLO: Efficient State-Space Perception and Local Spatial Reconstruction for UAV Small Object
Small-object detection in UAV imagery is challenged by weak visual evidence, ambiguous boundaries, dense object distributions, and complex backgrounds. Effective detection therefore requires long-range contextual information for target-background discrimination while preserving explicit local two-dimensional structures for accurate localization. These requirements arise at different stages of the detection pipeline and are not naturally addressed by a uniform feature-processing strategy. We propose Hybrid Dual-domain Mamba-YOLO (HDMamba-YOLO), a stage-wise heterogeneous SSM-CNN detector organi
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-19T14:47:57.000Z
First collected: 2026-09-23T10:01:48.231Z. This is not the publication date.