The DeepHealth toolkit: a key European free and open-source software for Deep Learning and Computer Vision ready to exploit heterogeneous HPC and cloud architectures
Marco Aldinucci,
David Atienza,
Federico Bolelli,
Mónica Caballero,
Iacopo Colonnelli,
José Flich,
Jon A. Gómez,
David González,
Costantino Grana,
Marco Grangetto,
Simone Leo,
Pedro López,
Dana Oniga,
Roberto Paredes,
Luca Pireddu,
Eduardo Quiñones,
Tatiana Silva,
Enzo Tartaglione,
Marina Zapater
Springer, page 183-202 - april 2022
Références BibTex
@InBook{AABCCFGGGGLLOPPQSTZ22,
author = {Aldinucci, M. and Atienza, D. and Bolelli, F. and Caballero, M. and Colonnelli, I. and Flich, J. and Gómez, J. and González, D. and Grana, C. and Grangetto, M. and Leo, S. and López, P. and Oniga, D. and Paredes, R. and Pireddu, L. and Quiñones, E. and Silva, T. and Tartaglione, E. and Zapater, M.},
title = {The DeepHealth toolkit: a key European free and open-source software for Deep Learning and Computer Vision ready to exploit heterogeneous HPC and cloud architectures},
pages = {183-202},
month = {april},
year = {2022},
publisher = {Springer},
note = {peer-reviewed; editors: Edward Curry, Sören Auer, Arne J. Berre, Andreas Metzger, Maria S. Perez, Sonja Zillner. DOI: 10.1007/978-3-030-78307-5_9},
type = {Chapter},
keywords = {deep learning, big data,cloud computing, hpc},
url = {https://publications.crs4.it/pubdocs/2022/AABCCFGGGGLLOPPQSTZ22},
}
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