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Francesco Barbato

As seen in: MDPI, Journal of Nuclear Medicine
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Articles

Computer Science > Computer Vision and Pattern Recognition

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By Matteo Caligiuri, Francesco Barbato, Pietro Zanuttigh
| arxiv.org
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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The Pelvic Rosetta Classification Project: An Interdisciplinary Proposal for a Lymph Node Map of the Pelvis in Prostate Cancer

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By Gernot Ortner, Francesco Barbato, Dirk Beyersdorff, Xenia Hoderlein
| Journal of Nuclear Medicine Verified
The Pelvic Rosetta Classification Project: An Interdisciplinary Proposal for a Lymph Node Map of the Pelvis in Prostate Cancer Gernot Ortner, Xenia Hoderlein, Francesco Barbato, Dirk Beyersdorff, Lars Budäus, Irene A.
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FedPromo: Federated Lightweight Proxy Models at the Edge Bring New Domains to Foundation Models

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By Francesco Barbato, Donald Shenaj, Umberto Michieli, Pietro Zanuttigh
| arxiv.org
[Submitted on 5 Aug 2025] Title:FedPromo: Federated Lightweight Proxy Models at the Edge Bring New Domains to Foundation Models View a PDF of the paper titled FedPromo: Federated Lightweight Proxy Models at the Edge Bring New Domains to Foundation Models, by Matteo Caligiuri and 4 other authors View PDF HTML (experimental) Abstract:Federated Learning (FL) is an established paradigm for training deep learning models on decentralized data.
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