2 citations · 3 across the 4 of their papers we have counts for
5 papers
Decoupled conditional contrastive learning with variable metadata for prostate lesion detection
Camille Ruppli, Pietro Gori, Roberto Ardon +1
Early diagnosis of prostate cancer is crucial for efficient treatment. Multi-parametric Magnetic Resonance Images (mp-MRI) are widely used for lesion detection. The Prostate Imagin…
Optimizing transformations for contrastive learning in a differentiable framework
Camille Ruppli, Pietro Gori, Roberto Ardon +1
Current contrastive learning methods use random transformations sampled from a large list of transformations, with fixed hyperparameters, to learn invariance from an unannotated da…
Leveraging Conditional Generative Models in a General Explanation Framework of Classifier Decisions
Martin Charachon, Paul-Henry Cournède, Céline Hudelot +1
Providing a human-understandable explanation of classifiers' decisions has become imperative to generate trust in their use for day-to-day tasks. Although many works have addressed…
Combining Similarity and Adversarial Learning to Generate Visual Explanation: Application to Medical Image Classification
Martin Charachon, Céline Hudelot, Paul-Henry Cournède +2
Explaining decisions of black-box classifiers is paramount in sensitive domains such as medical imaging since clinicians confidence is necessary for adoption. Various explanation a…
Classification of MRI data using Deep Learning and Gaussian Process-based Model Selection
Hadrien Bertrand, Matthieu Perrot, Roberto Ardon +1
The classification of MRI images according to the anatomical field of view is a necessary task to solve when faced with the increasing quantity of medical images. In parallel, adva…