Zobrazeno 1 - 10
of 195
pro vyhledávání: '"G Calvi"'
Autor:
M. Toppi, I. Avanzolini, L. Balconi, G. Battistoni, G. Calvi, M. De Simoni, Y. Dong, A. Fantoni, G. Franciosini, M. Marafini, M. Fischetti, V. Muccifora, S. Muraro, V. Patera, F. Ronchetti, A. Sarti, A. Sciubba, G. Traini, S. M. Valle, I. Mattei
Publikováno v:
Frontiers in Physics, Vol 9 (2021)
In Particle Therapy, safety margins are applied around the tumor to account for the beam range uncertainties and ensure an adequate dose coverage of the tumor volume during the therapy. The reduction of safety margins is in great demand in order to d
Externí odkaz:
https://doaj.org/article/840d6a2d7c2c4d1fb2589715a57ed50e
Publikováno v:
IEEE Signal Processing Magazine. 39:63-70
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::95d3fd7531cdea80795470c4d1ca0adb
https://doi.org/10.1109/msp.2022.3156744
https://doi.org/10.1109/msp.2022.3156744
Publikováno v:
Journal of Crohn's and Colitis. 17:i196-i197
Background Response and remission are among the most clinically relevant outcomes for patients treated for ulcerative colitis (UC). The aim of the study is comparing the cost of a sustained clinical response or remission (at 52 weeks’ follow-up) ac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3fc096b218b3829fb0d0aecce80c3521
https://doi.org/10.1093/ecco-jcc/jjac190.0156
https://doi.org/10.1093/ecco-jcc/jjac190.0156
Akademický článek
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Publikováno v:
IJCNN
Recurrent Neural Networks (RNNs) represent the de facto standard machine learning tool for sequence modelling, owing to their expressive power and memory. However, when dealing with large dimensional data, the corresponding exponential increase in th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c3dea0fca29154c99e2b8a87e7ba5952
https://doi.org/10.1109/ijcnn52387.2021.9534120
https://doi.org/10.1109/ijcnn52387.2021.9534120
Autor:
G. Calvi, F. Bello, B. Tagaste, Andrea Pella, Edoardo Mastella, Riccardo Via, Giorgia Meschini, Francesca Valvo, Ester Orlandi, Guido Baroni, Chiara Paganelli, Giulia Buizza, Mario Ciocca, G. Elisei, Rosalinda Ricotti, Giulia Fontana, Maria Rosaria Fiore
An Eye Tracking System (ETS) is used at CNAO for providing a stable and reproducible ocular proton therapy (OPT) set-up, featuring a fixation light (FL) and monitoring stereo-cameras embedded in a rigid case. The aim of this work is to propose an ETS
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dc1629bbedc012c9915df51acaa35f92
http://hdl.handle.net/11311/1167049
http://hdl.handle.net/11311/1167049
Publikováno v:
Recent Trends in Learning From Data ISBN: 9783030438821
The exponentially increasing availability of big and streaming data comes as a direct consequence of the rapid development and widespread use of multi-sensor technology. The quest to make sense of such large volume and variety of that has both highli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1f7e2849b2aeda1517a1bb1cb7bb22c4
https://doi.org/10.1007/978-3-030-43883-8_4
https://doi.org/10.1007/978-3-030-43883-8_4
Publikováno v:
ICASSP
Past decades have witnessed excessive use of the Support Vector Machines (SVMs) in financial contexts. Despite their success, given the inherently multivariate nature of financial indices, the vector-based nature of SVM will inevitably lead to a loss
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::56dd936365a1c3e9cb43629750cb02c0
https://doi.org/10.1109/icassp.2019.8683383
https://doi.org/10.1109/icassp.2019.8683383
Publikováno v:
Signal Processing. 180:107862
Tensor decompositions represent a class of tools for analysing datasets of high dimensionality and variety in a natural manner, with the Canonical Polyadic Decomposition (CPD) serving as a main pillar. While the notion of CPD is closely intertwined w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4c79182c8db8aa5212f03d7b6e61c121
https://doi.org/10.1016/j.sigpro.2020.107862
https://doi.org/10.1016/j.sigpro.2020.107862
Publikováno v:
EUSIPCO
Tensor networks (TNs) have been earning considerable attention as multiway data analysis tools owing to their ability to tackle the curse of dimensionality through the representation of large-scale tensors via smaller-scale interconnections of their
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d8fa0e27912362304f87ba4021ab9111
https://doi.org/10.23919/eusipco.2018.8553605
https://doi.org/10.23919/eusipco.2018.8553605