Search Results for author:
Found 3 papers, 2 papers with code
Enhancing Privacy in Federated Learning: Secure Aggregation for Real-World Healthcare Applications
Deploying federated learning (FL) in real-world scenarios, particularly in healthcare, poses challenges in communication and security.
Benchmarking Collaborative Learning Methods Cost-Effectiveness for Prostate Segmentation
To the best of our knowledge, this is the first work in which CBM, such as label fusion techniques, are used to solve a problem of collaborative learning.
Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications
The real-world implementation of federated learning is complex and requires research and development actions at the crossroad between different domains ranging from data science, to software programming, networking, and security.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
