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Conditional Alignment and Uniformity for Contrastive Learning with Continuous Proxy Labels
Benoit Dufumier, Pietro Gori, Julie Victor +2
Contrastive Learning has shown impressive results on natural and medical images, without requiring annotated data. However, a particularity of medical images is the availability of…
UCSL : A Machine Learning Expectation-Maximization framework for Unsupervised Clustering driven by Supervised Learning
Robin Louiset, Pietro Gori, Benoit Dufumier +3
Subtype Discovery consists in finding interpretable and consistent sub-parts of a dataset, which are also relevant to a certain supervised task. From a mathematical point of view,…
Contrastive Learning with Continuous Proxy Meta-Data for 3D MRI Classification
Benoit Dufumier, Pietro Gori, Julie Victor +8
Traditional supervised learning with deep neural networks requires a tremendous amount of labelled data to converge to a good solution. For 3D medical images, it is often impractic…
Benchmarking CNN on 3D Anatomical Brain MRI: Architectures, Data Augmentation and Deep Ensemble Learning
Benoit Dufumier, Pietro Gori, Ilaria Battaglia +3
Deep Learning (DL) and specifically CNN models have become a de facto method for a wide range of vision tasks, outperforming traditional machine learning (ML) methods. Consequently…