Julie Victor

Contrastive Learning with Continuous Proxy Meta-Data for 3D MRI Classification

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 impractical to build a...

Conditional Alignment and Uniformity for Contrastive Learning with Continuous Proxy Labels

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 meta-data (such...

Contrastive Learning with Continuous Proxy Meta-data for 3D MRI Classification

Benchmarking CNN on 3D Anatomical Brain MRI: Architectures, Data Augmentation and Deep Ensemble Learning

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, they drew a...