Usman Ali

Tiling to transfer: patch-level contrastive learning framework for cross-dataset generalization on downstream diabetic retinopathy grading tasks

This study presents a patch-based contrastive learning framework (Patch-SimCLR) designed to improve the generalizability and calibration of diabetic retinopathy classification across heterogeneous fundus datasets. By extracting overlapping, and non-overlapping patches and leveraging contrastive pretraining, the model l...