Optimized Hard Exudate Detection with Supervised Contrastive Learning

The author presents a novel supervised contrastive learning framework to optimize hard exudate segmentation by addressing challenges related to inconsistent shapes and indistinct boundaries. The main thesis is that the proposed method enhances lesion detection accuracy through patch-wise density contrasting and discriminative edge inspection.