Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Dario Aragona"'
Publikováno v:
ACM SIGAPP Applied Computing Review. 21:5-18
In this paper we present C o R o NN a a deep sequential framework for epidemic prediction that leverages a flexible combination of sequential and convolutional components to analyse the transmission of COVID-19 and, perhaps, other undiscovered viruse
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::749551286e24c55d652b546e6f2ee9c6
https://doi.org/10.1145/3493499.3493500
https://doi.org/10.1145/3493499.3493500
Autor:
Paola Velardi, Bardh Prenkaj, Dario Aragona, Alessandro Flaborea, Fabio Galasso, Saverio Gravina, Luca Podo, Emilia Reda
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0efd74b624c50d68d4dc671bf05ba6b4
https://doi.org/10.2139/ssrn.4047839
https://doi.org/10.2139/ssrn.4047839
Autor:
Bardh Prenkaj, Dario Aragona, Alessandro Flaborea, Fabio Galasso, Saverio Gravina, Luca Podo, Emilia Reda, Paola Velardi
Publikováno v:
Artificial Intelligence in Medicine. 135:102454
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f5254f2fad1a2fa680401c9fb0599fa
https://doi.org/10.1016/j.artmed.2022.102454
https://doi.org/10.1016/j.artmed.2022.102454
Publikováno v:
SAC
We propose CoRoNNa, a deep framework for epidemic prediction to analyse the spread of COVID-19 and, potentially, of other unknown viruses, based on a flexible integration of sequential and convolutional components. Importantly, our framework is gener
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ea36ac38ea2ab3608f41ee59908c61d5
https://doi.org/10.1145/3412841.3441883
https://doi.org/10.1145/3412841.3441883
