A Weakly Supervised Segmentation Algorithm Based on Local–Global Class Labelling Comparison
A single-stage weakly supervised segmentation algorithm based on local–global class labelling comparison that effectively improves the completeness of target activation regions and suppresses background noise, and it maintains strong generalization for slender, small and texture-sparse objects.