A ViT-to-CNN knowledge-distillation pipeline for retinal disease classification is reported with 89% student accuracy, but the deployment claim, baseline comparison, and reported numbers are internally unreliable.
as well as more rare diseases
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Cross-Architecture Knowledge Distillation (KD) for Retinal Fundus Image Anomaly Detection on NVIDIA Jetson Nano
A ViT-to-CNN knowledge-distillation pipeline for retinal disease classification is reported with 89% student accuracy, but the deployment claim, baseline comparison, and reported numbers are internally unreliable.