Zobrazeno 1 - 10
of 162
pro vyhledávání: '"Antonio Pietrabissa"'
Publikováno v:
IEEE Access, Vol 12, Pp 30638-30652 (2024)
The evaluation of time and frequency domain measures of coupling and causality relies on the parametric representation of linear multivariate processes. The study of temporal dependencies among time series is based on the identification of a Vector A
Externí odkaz:
https://doaj.org/article/95869a48c8a64229bc2dcefef5734ddf
Publikováno v:
IEEE Access, Vol 11, Pp 80613-80623 (2023)
This paper presents a Federated Learning (FL) algorithm that allows the decentralization of all FL solutions that employ a model-averaging procedure. The proposed algorithm proves to be capable of attaining faster convergence rates and no performance
Externí odkaz:
https://doaj.org/article/315f660d58c7443880e59aaac266bb4d
Publikováno v:
Machine Learning: Science and Technology, Vol 5, Iss 3, p 035059 (2024)
Chaos detection is the problem of identifying whether a series of measurements is being sampled from an underlying set of chaotic dynamics. The unavoidable presence of measurement noise significantly affects the performance of chaos detectors, as dis
Externí odkaz:
https://doaj.org/article/984fb5e56ecc4b178b1bde411ba04938
Publikováno v:
IEEE Access, Vol 10, Pp 92681-92691 (2022)
Federated Learning (FL) is a distributed machine learning technique which enables local learning of global machine learning models without the need of exchanging data. The original FL algorithm, Federated Averaging (FedAvg), is extended in this work
Externí odkaz:
https://doaj.org/article/5485c628e0b64a16b28ccffd13b2c5ec
Autor:
Federico Baldisseri, Andrea Wrona, Danilo Menegatti, Antonio Pietrabissa, Stefano Battilotti, Claudia Califano, Andrea Cristofaro, Paolo Di Giamberardino, Francisco Facchinei, Laura Palagi, Alessandro Giuseppi, Francesco Delli Priscoli
Publikováno v:
Healthcare, Vol 11, Iss 18, p 2603 (2023)
Portal hypertension is a complex medical condition characterized by elevated blood pressure in the portal venous system. The conventional diagnosis of such disease often involves invasive procedures such as liver biopsy, endoscopy, or imaging techniq
Externí odkaz:
https://doaj.org/article/8d554ea7ee4145a0998da243f2ecec4e
Autor:
Danilo Menegatti, Alessandro Giuseppi, Francesco Delli Priscoli, Antonio Pietrabissa, Alessandro Di Giorgio, Federico Baldisseri, Mattia Mattioni, Salvatore Monaco, Leonardo Lanari, Martina Panfili, Vincenzo Suraci
Publikováno v:
Healthcare, Vol 11, Iss 15, p 2199 (2023)
Data-driven algorithms have proven to be effective for a variety of medical tasks, including disease categorization and prediction, personalized medicine design, and imaging diagnostics. Although their performance is frequently on par with that of cl
Externí odkaz:
https://doaj.org/article/7790a50ef41b4456a68086712edb4662
Autor:
Junhyeong Kim, Guido Casati, Nicolas Cassiau, Antonio Pietrabissa, Alessandro Giuseppi, Dong Yan, Emilio Calvanese Strinati, Marjorie Thary, Danping He, Ke Guan, Heesang Chung, Ilgyu Kim
Publikováno v:
ETRI Journal, Vol 42, Iss 5, Pp 669-688 (2020)
5G AgiLe and fLexible integration of SaTellite And cellulaR (5G‐ALLSTAR) is a Korea‐Europe (KR‐EU) collaborative project for developing multi‐connectivity (MC) technologies that integrate cellular and satellite networks to provide seamless, r
Externí odkaz:
https://doaj.org/article/7af0c916972d4fbeb16e56d710237003
Autor:
Emilio Calvanese Strinati, Sergio Barbarossa, Taesang Choi, Antonio Pietrabissa, Alessandro Giuseppi, Emanuele De Santis, Josep Vidal, Zdenek Becvar, Thomas Haustein, Nicolas Cassiau, Francesca Costanzo, Junhyeong Kim, Ilgyu Kim
Publikováno v:
ETRI Journal, Vol 42, Iss 5, Pp 643-657 (2020)
AbstractSixth generation will exploit satellite, aerial, and terrestrial platforms jointly to improve radio access capability and unlock the support of on‐demand edge cloud services in three‐dimensional (3D) space, by incorporating mobile edge co
Externí odkaz:
https://doaj.org/article/a94346d5717a421f8f6b5041a773e913
Autor:
Yuri Antonacci, Ludovico Minati, Luca Faes, Riccardo Pernice, Giandomenico Nollo, Jlenia Toppi, Antonio Pietrabissa, Laura Astolfi
Publikováno v:
PeerJ Computer Science, Vol 7, p e429 (2021)
One of the most challenging problems in the study of complex dynamical systems is to find the statistical interdependencies among the system components. Granger causality (GC) represents one of the most employed approaches, based on modeling the syst
Externí odkaz:
https://doaj.org/article/c94127fe36fe479791ae6c610d159591
Autor:
Alessandro Giuseppi, Roberto Germanà, Federico Fiorini, Francesco Delli Priscoli, Antonio Pietrabissa
Publikováno v:
Drones, Vol 5, Iss 4, p 130 (2021)
Fire monitoring and early detection are critical tasks in which Unmanned Aerial Vehicles (UAVs) are commonly employed. This paper presents a system to plan the drone patrolling schedule according to a real-time estimation of a fire propagation index
Externí odkaz:
https://doaj.org/article/04e6adf5c00a4fd198ce622918d10318