Prototypical Networks with ImageNet-pretrained ResNet backbones classify kidney stone subtypes from endoscopic patches as accurately with 25% of the training data as a conventional ResNet trained on the full dataset.
Evaluation and understanding of automated urinary stone recognition methods
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Evaluation of Few-Shot Learning Methods for Kidney Stone Type Recognition in Ureteroscopy
Prototypical Networks with ImageNet-pretrained ResNet backbones classify kidney stone subtypes from endoscopic patches as accurately with 25% of the training data as a conventional ResNet trained on the full dataset.