Zobrazeno 1 - 10
of 325
pro vyhledávání: '"Luca Lanzi"'
Publikováno v:
Computers & Education: X Reality, Vol 2, Iss , Pp 100014- (2023)
Immersive Virtual Reality technology has recently gained significant attention and is expanding its applications to various fields. It also has many advantages in education, as it allows to both simplify the explanation of complex topics through thei
Externí odkaz:
https://doaj.org/article/60a1cc138bc54582a192680bebd03a10
Autor:
Camilla Colombo, Nicoletta Di Blas, Ioannis Gkolias, Pier Luca Lanzi, Daniele Loiacono, Erica Stella
Publikováno v:
IEEE Access, Vol 8, Pp 85162-85178 (2020)
Space debris represents a threat to space missions and operational satellites. Failing to control its growth might lead to the inability to use near-Earth space. However, this issue is still largely unknown to most people. In this paper, we present a
Externí odkaz:
https://doaj.org/article/d3d2121486594119b6ea1a6ba5188431
Autor:
Monica Clerici, Paolo Boffi, Pier Luca Lanzi, Lilia Coppola, Cristina Murone, Alberto Gallace
Publikováno v:
2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct).
Autor:
Eleonora Chitti, N. Alberto Borghese, Federica Anello, Pier Luca Lanzi, Fabrizia Corona, Giovanni Filocamo, Michaela Foa, Antonella Petaccia, Amalia Lopopolo
Publikováno v:
2022 IEEE 10th International Conference on Serious Games and Applications for Health(SeGAH).
Publikováno v:
SSRN Electronic Journal.
Autor:
Giovanni Filocamo, N. Alberto Borghese, Pier Luca Lanzi, Michaela Foa, Federica Anello, Antonella Petaccia, Fabrizia Corona, Amalia Lopopolo, Eleonora Chitti
Publikováno v:
SEGAH
In recent years new technologies have been developed to track user's motions, as the Leap Motion Controller for hands and wrist tracking. We propose a framework for children's hand, wrist and forearm rehabilitation at home and at hospital designed an
Publikováno v:
IJCNN
Chest X-ray (CXR) is perhaps the most frequently-performed radiological investigation globally. In this work, we present and study several machine learning approaches to develop automated CXR diagnostic models. In particular, we trained several Convo
Autor:
Luca Mainardi, Pier Luca Lanzi, Francesco Amigoni, Arturo Chiti, Martina Sollini, Noemi Gozzi, Daniele Loiacono, Margarita Kirienko, Gaia Ninatti, Edoardo Giacomello
Publikováno v:
European Journal of Nuclear Medicine and Molecular Imaging
Purpose The present scoping review aims to assess the non-inferiority of distributed learning over centrally and locally trained machine learning (ML) models in medical applications. Methods We performed a literature search using the term “distribu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fdac3cffa7355cbee8987b016bfaba8a
http://hdl.handle.net/11311/1204492
http://hdl.handle.net/11311/1204492