Camouflaged Object Detection using 3 Yolo

Vinay K Awasthi; Max Mayberg; Yin-Li Liu

doi:10.20944/preprints202406.1559.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 19 June 2024 / Approved: 21 June 2024 / Online: 24 June 2024 (09:47:32 CEST)

Real time camouflaged object detection so far using CAMO or COD10K datset has been able to achieve mAP50 less than 64%. We present a fourier transfom and Milkyway filament extraction based method extracting shape and edges of camouflaged object, achieving 88%+ mAP50 while continuing to deliver real time detection using YOLOv8s based models. This allows for search and rescue of wilelife and humans in smoke, fog, natural disasters possible by combining low compute Yolov8s model on headup display for rescue workers such as firefighters, first reponders etc.

Fourier convolution, CNN, Yolo, Scatter2d

Computer Science and Mathematics, Computer Vision and Graphics

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Camouflaged Object Detection using 3 Yolo

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