Real-time detection of outdoor non-obvious anthropogenic trace via texture contrast learning
Experiments demonstrate that the proposed self-supervised machine vision framework effectively segments camouflaged traces in low-quality, unlabeled outdoor images captured by a mobile robot, outperforming existing COD models in adaptation speed and segmentation accuracy on a challenging custom rescue dataset.