Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Pietro Fronte"'
Predicting WNV Circulation in Italy Using Earth Observation Data and Extreme Gradient Boosting Model
Autor:
Luca Candeloro, Carla Ippoliti, Federica Iapaolo, Federica Monaco, Daniela Morelli, Roberto Cuccu, Pietro Fronte, Simone Calderara, Stefano Vincenzi, Angelo Porrello, Nicola D’Alterio, Paolo Calistri, Annamaria Conte
Publikováno v:
Remote Sensing, Vol 12, Iss 18, p 3064 (2020)
West Nile Disease (WND) is one of the most spread zoonosis in Italy and Europe caused by a vector-borne virus. Its transmission cycle is well understood, with birds acting as the primary hosts and mosquito vectors transmitting the virus to other bird
Externí odkaz:
https://doaj.org/article/4d2e538bc4b94124ac89200e6839eeec
Prioritization of activities is one of the many facets in digital products management. In this study, we propose an alternative point of view on Portofolio Projects Management, in order better understand their relationship between performance and imp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2dba2c0889145fabb5de6f4c9507e830
https://doi.org/10.3233/faia220312
https://doi.org/10.3233/faia220312
Predicting WNV Circulation in Italy Using Earth Observation Data and Extreme Gradient Boosting Model
Autor:
F. Iapaolo, Roberto Cuccu, Simone Calderara, Federica Monaco, Daniela Morelli, Pietro Fronte, Stefano Vincenzi, Paolo Calistri, Luca Candeloro, Nicola D'Alterio, Annamaria Conte, Carla Ippoliti, Angelo Porrello
Publikováno v:
Remote Sensing, Vol 12, Iss 3064, p 3064 (2020)
Remote Sensing; Volume 12; Issue 18; Pages: 3064
Remote Sensing; Volume 12; Issue 18; Pages: 3064
West Nile Disease (WND) is one of the most spread zoonosis in Italy and Europe caused by a vector-borne virus. Its transmission cycle is well understood, with birds acting as the primary hosts and mosquito vectors transmitting the virus to other bird
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9ba3580980cc7577e689fb2f6821c7e2
https://www.mdpi.com/2072-4292/12/18/3064
https://www.mdpi.com/2072-4292/12/18/3064
Autor:
Roberto Cuccu, Pietro Fronte, Stefano Vincenzi, Pietro Buzzega, Simone Calderara, Marco Cipriano, Carla Ippoliti, Annamaria Conte, Angelo Porrello
Publikováno v:
ICPR
The recent growth in the number of satellite images fosters the development of effective deep-learning techniques for Remote Sensing (RS). However, their full potential is untapped due to the lack of large annotated datasets. Such a problem is usuall
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::face04a71f762cf4bd51bf8ccee2ba28