A proof-of-concept multimodal pipeline using LiDAR, visible-thermal fusion, AOS, and fine-tuned YOLOv5 reports mAP of ~0.83 on thermal classes and notes limited LiDAR penetration plus improved visibility from fusion and AOS in forest settings.
Airborne Optical Sectioning for Object Detection in Cluttered Environments,
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Multimodal Object Detection Under Sparse Forest-Canopy Occlusion
A proof-of-concept multimodal pipeline using LiDAR, visible-thermal fusion, AOS, and fine-tuned YOLOv5 reports mAP of ~0.83 on thermal classes and notes limited LiDAR penetration plus improved visibility from fusion and AOS in forest settings.