Barbieri, Luca - Search Results - CERN Document Server

Search collections:

Sort by:	Display results:	Output format:

CERN Document Server	6 records found	Search took 0.95 seconds.

A Federated Learning Platform as a Service for Advancing Stroke Management in European Clinical Centers / Santos, Diogo Reis (CERN) ; Aillet, Albert Sund (CERN) ; Boiano, Antonio (Unlisted, IT) ; Milasheuski, Usevalad (Unlisted, IT ; CNR, Italy) ; Giusti, Lorenzo (CERN) ; Gennaro, Marco Di (Unlisted, IT) ; Kianoush, Sanaz (CNR, Italy) ; Barbieri, Luca (Unlisted, IT) ; Nicoli, Monica (CERN) ; Carminati, Michele (Unlisted, IT) et al.
The rapid evolution of artificial intelligence (AI) technologies holds transformative potential for the healthcare sector. [...]
2024 - 7.

Detailed record

A Close Look at the Communication Efficiency and the Energy Footprints of Robust Federated Learning in Industrial IoT / Barbieri, Luca (Milan, Polytech.) ; Kianoush, Sanaz (CNR, Milan) ; Nicoli, Monica (Milan, Polytech.) ; Serio, Luigi (CERN) ; Savazzi, Stefano (CNR,Milan)
Federated learning (FL) can be used to distribute machine learning (ML) tasks across edge and Internet of Things (IoT) devices with limited resources. FL provides an alternative and much more practical solution to classical artificial intelligence (AI), which requires moving large data volumes to energy-hungry data centers. [...]
2025 - 21 p. - Published in : IEEE Internet of Things Journal 12 (2025) 15130-15150 Fulltext: PDF; External link: Fulltext

Detailed record

Fast Emitting Nanocomposites for High‐Resolution ToF‐PET Imaging Based on Multicomponent Scintillators / Orfano, Matteo (Milan Bicocca U.) ; Pagano, Fiammetta (CERN ; Milan Bicocca U.) ; Mattei, Ilaria (INFN, Milan) ; Cova, Francesca (Milan Bicocca U.) ; Secchi, Valeria (Milan Bicocca U.) ; Bracco, Silvia (Milan Bicocca U.) ; Rogers, Edith (Cranfield U.) ; Barbieri, Luca (Milan Bicocca U.) ; Lorenzi, Roberto (Milan Bicocca U.) ; Bizarri, Gregory (Cranfield U.) et al.
AbstractTime‐of‐Flight Positron Emission Tomography (ToF‐PET) is a medical imaging technique, based on the detection of two back‐to‐back γ‐photons generated from radiotracers injected into the body. Its limit is the ability of employed scintillation detectors to discriminate in time the arrival of γ‐pairs, that is, the coincidence time resolution (CTR). [...]
2024 - 11 p. - Published in : Adv. Mater. Technol. 9 (2024) 2302075 Fulltext: PDF;

Detailed record

A Carbon Tracking Model for Federated Learning: Impact of Quantization and Sparsification / Barbieri, Luca (Milan, Polytech.) ; Savazzi, Stefano ; Kianoush, Sanaz ; Nicoli, Monica (Milan, Polytech.) ; Serio, Luigi (CERN)
Federated Learning (FL) methods adopt efficient communication technologies to distribute machine learning tasks across edge devices, reducing the overhead in terms of data storage and computational complexity compared to centralized solutions. Rather than moving large data volumes from producers (sensors, machines) to energy-hungry data centers, raising environmental concerns due to resource demands, FL provides an alternative solution to mitigate the energy demands of several learning tasks while enabling new Artificial Intelligence of Things (AIoT) applications. [...]
arXiv:2310.08087.- 2023-11-06 - 6 p. - Published in : 10.1109/CAMAD59638.2023.10478391 Fulltext: PDF;
In : IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD 2023), Edinburgh, Scotland, 6-8 Nov 2023, pp.213-218

Detailed record

A Secure and Trustworthy Network Architecture for Federated Learning Healthcare Applications / Boiano, Antonio (Milan, Polytech.) ; Di Gennaro, Marco (Milan, Polytech.) ; Barbieri, Luca (Milan, Polytech.) ; Carminati, Michele (Milan, Polytech.) ; Nicoli, Monica (Milan, Polytech.) ; Redondi, Alessandro (Milan, Polytech.) ; Savazzi, Stefano (IFN, Rome) ; Aillet, Albert Sund (CERN) ; Santos, Diogo Reis (CERN) ; Serio, Luigi (CERN)
Federated Learning (FL) has emerged as a promising approach for privacy-preserving machine learning, particularly in sensitive domains such as healthcare. [...]
arXiv:2404.11698. - 6 p.
Fulltext

Detailed record

Decentralized Federated Learning for Healthcare Networks: A Case Study on Tumor Segmentation / Camajori Tedeschini, Bernardo (Milan, Polytech.) ; Savazzi, Stefano (ISTP, Milan) ; Stoklasa, Roman (CERN) ; Barbieri, Luca (Milan, Polytech.) ; Stathopoulos, Ioannis (CERN) ; Nicoli, Monica (Milan, Polytech.) ; Serio, Luigi (CERN)
Smart healthcare relies on artificial intelligence (AI) functions for learning and analysis of patient data. Since large and diverse datasets for training of Machine Learning (ML) models can rarely be found in individual medical centers, classical centralized AI requires moving privacy-sensitive data from medical institutions to data centers that process the fused information. [...]
2022 - 16 p. - Published in : IEEE Access 10 (2022) 8693-8708 Fulltext: PDF;

Detailed record

See also: similar author names
1	Barbieri, L
1	Barbieri, Lorenzo

Interested in being notified about new results for this query?
Set up a personal email alert or subscribe to the RSS feed.

Haven't found what you were looking for? Try your search on other servers:
Barbieri, Luca in Amazon Barbieri, Luca in CERN EDMS Barbieri, Luca in CERN Intranet Barbieri, Luca in CiteSeer Barbieri, Luca in Google Books Barbieri, Luca in Google Scholar Barbieri, Luca in Google Web Barbieri, Luca in IEC	Barbieri, Luca in IHS Barbieri, Luca in INSPIRE Barbieri, Luca in ISO Barbieri, Luca in KISS Books/Journals Barbieri, Luca in KISS Preprints Barbieri, Luca in NEBIS Barbieri, Luca in SLAC Library Catalog Barbieri, Luca in Scirus

CERN Document Server

Access articles, reports and multimedia content in HEP

Main menu

CERN Accelerating science