Accurately predicting traffic risks at urban intersections is essential for improving road safety. While traditional models use data sources like road traffic conditions, geometry, and signals, they ...

Abstract: Federated learning is an important distributed machine learning paradigm. This study proposes a privacy-preserving data augmentation model for federated learning of heterogeneous data, which ...