Clustered Federated Learning for Image Classification

Clustered Federated Learning (CFL) in image classification involves grouping clients into clusters based on data similarity. Each cluster trains a local model on its data, and these models are then aggregated to form a global model. This approach enhances model performance by addressing data heterogeneity and improving personalization.