Search Results for author: Riccardo Taiello

Found 3 papers, 2 papers with code

Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications

no code implementations24 Apr 2023 Francesco Cremonesi, Marc Vesin, Sergen Cansiz, Yannick Bouillard, Irene Balelli, Lucia Innocenti, Santiago Silva, Samy-Safwan Ayed, Riccardo Taiello, Laetita Kameni, Richard Vidal, Fanny Orlhac, Christophe Nioche, Nathan Lapel, Bastien Houis, Romain Modzelewski, Olivier Humbert, Melek Önen, Marco Lorenzi

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.

Federated Learning

Privacy Preserving Image Registration

2 code implementations17 May 2022 Riccardo Taiello, Melek Önen, Francesco Capano, Olivier Humbert, Marco Lorenzi

Image registration is a key task in medical imaging applications, allowing to represent medical images in a common spatial reference frame.

Affine Image Registration Cubic splines Image Registration +2

Study on Transfer Learning Capabilities for Pneumonia Classification in Chest-X-Rays Image

1 code implementation6 Oct 2021 Danilo Avola, Andrea Bacciu, Luigi Cinque, Alessio Fagioli, Marco Raoul Marini, Riccardo Taiello

Over the last year, the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and its variants have highlighted the importance of screening tools with high diagnostic accuracy for new illnesses such as COVID-19.

Transfer Learning

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