Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Dalila Ressi"'
Publikováno v:
AIxIA 2022 – Advances in Artificial Intelligence ISBN: 9783031271809
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::31684818bacb21e63e3f4e69bb04581a
https://hdl.handle.net/11390/1244389
https://hdl.handle.net/11390/1244389
Publikováno v:
AIxIA 2021 – Advances in Artificial Intelligence ISBN: 9783031084201
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8652051eb50389bd7b3c0a0e6cf0c2e9
http://hdl.handle.net/10278/5004312
http://hdl.handle.net/10278/5004312
Autor:
Luca Cosmo, Andrea Albarelli, Dalila Ressi, Filippo Bergamasco, Andrea Gasparetto, Mara Pistellato
Publikováno v:
ICPR
Among several structured light approaches, phase shift is the most widely adopted in real-world 3D reconstruction devices. This is mainly due to its high accuracy, strong resilience to noise and straightforward implementation. However, Phase shift al
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c3ccb654fe0631e9552198f98150d682
https://doi.org/10.1109/icpr.2018.8546052
https://doi.org/10.1109/icpr.2018.8546052
Autor:
Dalila Ressi, Marco Boschetti, Enrico Ursella, Mara Pistellato, Luca Cosmo, Filippo Bergamasco, Andrea Albarelli, Andrea Gasparetto
Publikováno v:
ICPR
Within modern Deep Learning setups, data augmentation is the weapon of choice when dealing with narrow datasets or with a poor range of different samples. However, the benefits of data augmentation are abysmal when applied to a dataset which is inher
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b91936f5b6bc2470a0b7b8d86b97ff90
https://doi.org/10.1109/icpr.2018.8545812
https://doi.org/10.1109/icpr.2018.8545812