research
∙
08/18/2023
Decoupled conditional contrastive learning with variable metadata for prostate lesion detection
Early diagnosis of prostate cancer is crucial for efficient treatment. M...
share
research
∙
07/27/2022
Optimizing transformations for contrastive learning in a differentiable framework
Current contrastive learning methods use random transformations sampled ...
research
∙
06/21/2021
Leveraging Conditional Generative Models in a General Explanation Framework of Classifier Decisions
Providing a human-understandable explanation of classifiers' decisions h...
research
∙
12/14/2020
Combining Similarity and Adversarial Learning to Generate Visual Explanation: Application to Medical Image Classification
Explaining decisions of black-box classifiers is paramount in sensitive ...
research
∙
01/16/2017
