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Ophthalmic VQA models can be made more accurate and transparent by explicitly grounding them in spatially-localized lesion evidence, a crucial step towards clinical interpretability.
Randomly throwing distortions at your watermarking model during training? Meta-FC shows meta-learning a better way, boosting robustness by up to 4.71% against combined distortions.
