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ProtoMedX: Towards Explainable Multi-Modal Prototype Learning for Bone Health Classification
Alvaro Lopez Pellicer, Andre Mariucci, Plamen Angelov +2
Bone health studies are crucial in medical practice for the early detection and treatment of Osteopenia and Osteoporosis. Clinicians usually make a diagnosis based on densitometry…
Prototype-Based Continual Learning with Label-free Replay Buffer and Cluster Preservation Loss
Agil Aghasanli, Yi Li, Plamen Angelov
Continual learning techniques employ simple replay sample selection processes and use them during subsequent tasks. Typically, they rely on labeled data. In this paper, we depart f…
COMIX: Compositional Explanations using Prototypes
Sarath Sivaprasad, Dmitry Kangin, Plamen Angelov +1
Aligning machine representations with human understanding is key to improving interpretability of machine learning (ML) models. When classifying a new image, humans often explain t…