Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Ernesto Biempica"'
Publikováno v:
IEEE Access, Vol 8, Pp 40573-40598 (2020)
The advent of machine learning (ML) methods for the industry has opened new possibilities in the automotive domain, especially for Advanced Driver Assistance Systems (ADAS). These methods mainly focus on specific problems ranging from traffic sign an
Externí odkaz:
https://doaj.org/article/8f4dd80b7df54083bfc5af2c6907588b
Publikováno v:
Personal and Ubiquitous Computing. 26:1355-1372
The use of capacitive sensors in the automotive context opens new possibilities in the development of new interfaces for machine interaction with the vehicle occupants. Large smart surfaces with gesture recognition will possibly be part of such new i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bda0e1cbab448c4ea16db0b35fef529b
https://doi.org/10.1007/s00779-020-01472-6
https://doi.org/10.1007/s00779-020-01472-6
Publikováno v:
IEEE Access, Vol 8, Pp 40573-40598 (2020)
The advent of machine learning (ML) methods for the industry has opened new possibilities in the automotive domain, especially for Advanced Driver Assistance Systems (ADAS). These methods mainly focus on specific problems ranging from traffic sign an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::03ed871eaeea3c569df90cae6704dbbd
https://doi.org/10.1109/access.2020.2976513
https://doi.org/10.1109/access.2020.2976513
Publikováno v:
ICMLA
Neural Architecture Search (NAS), which allows for automatically developing neural networks, has been mostly devoted to performance on a single metric, usually accuracy. New approaches have added more objectives, such as model size, in order to find
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::28b755aa92b5bbc1bd5acd10dde17c0c
https://doi.org/10.1109/icmla51294.2020.00011
https://doi.org/10.1109/icmla51294.2020.00011
Publikováno v:
DDECS
Capacitive sensing offers new possibilities for HMI product development. Its short range of interaction entails robustness against environmental noise and its flexibility for integration makes it a genuine technology for embedded systems. In the auto
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::53595425f2e3dfcfdb47dc73606823cc
https://doi.org/10.1109/ddecs50862.2020.9095748
https://doi.org/10.1109/ddecs50862.2020.9095748
Publikováno v:
MLSP
This paper demonstrates a semi-supervised learning approach to frame-level proximity and touch recognition with machine learning algorithms for sequential modeling. We focus on capacitive sensing, which is employable in low cost embedded devices and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e3dcf9c2905083d71a042b2f44ee6e06
https://doi.org/10.1109/mlsp.2018.8516922
https://doi.org/10.1109/mlsp.2018.8516922
Autor:
Castells-Rufas, David, Borrego-Carazo, Juan, Carrabina, Jordi, Naqui, Jordi, Biempica, Ernesto
Publikováno v:
Personal & Ubiquitous Computing; Dec2022, Vol. 26 Issue 6, p1355-1372, 18p