Federated learning (FL) allows hospitals and medical centers to train models without sharing patient data. Instead of sending data to a central server, each institution trains the model locally and ...

CRAS aims to address inter-class interference and intra-class overlap in multi-class anomaly detection through center-aware residual learning and distance-guided anomaly synthesis. This repository ...