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Found 3 papers, 1 papers with code
Decoupled conditional contrastive learning with variable metadata for prostate lesion detection
Early diagnosis of prostate cancer is crucial for efficient treatment.
Optimizing transformations for contrastive learning in a differentiable framework
Following previous works that introduce a small amount of supervision, we propose a framework to find optimal transformations for contrastive learning using a differentiable transformation network.
Combining Similarity and Adversarial Learning to Generate Visual Explanation: Application to Medical Image Classification
From a given classifier, we train two generators to produce from an input image the so called similar and adversarial images.
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