arXiv cs.LG
· Papers
QFedPolyp: A Communication- and Inference-Efficient Federated Learning Framework for Polyp Segmentation
arXiv:2607.22743v1 Announce Type: new Abstract: Background and Objective: Automatic polyp segmentation supports computer-aided diagnosis and early colorectal cancer detec- tion. Centralized deep learning requires hospitals to share sensitive medical data, while federated learning preserves privacy but introduces high c