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Found 2 papers, 1 papers with code
Discrepancy-based Active Learning for Weakly Supervised Bleeding Segmentation in Wireless Capsule Endoscopy Images
Specifically, to liberate labor, we design a novel discrepancy decoder model and a CAMPUS (CAM, Pseudo-label and groUnd-truth Selection) criterion to replace the noisy CAMs with accurate model predictions and a few human labels.
Categorical Relation-Preserving Contrastive Knowledge Distillation for Medical Image Classification
With the contribution of the CCD and CRP, our CRCKD algorithm can distill the relational knowledge more comprehensively.
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