Zobrazeno 1 - 10
of 43
pro vyhledávání: '"Choubeila Maaoui"'
Publikováno v:
IEEE Access, Vol 8, Pp 56992-57002 (2020)
Innovative technologies and naturalistic driving data sources provide a great potential to develop reliable autonomous driving systems. Understanding the behaviors of surrounding vehicles is essential for improving safety and mobility of autonomous v
Externí odkaz:
https://doaj.org/article/34fe2daec43a45dabbd4306eeb9d5d77
Publikováno v:
Applied Sciences, Vol 12, Iss 19, p 9582 (2022)
Photoplethysmography is a method to visualize the variation in blood volume within tissues with light. The signal obtained has been used for the monitoring of patients, interpretation for diagnosis or for extracting other physiological variables (e.g
Externí odkaz:
https://doaj.org/article/0768e86f2a344bb886d3c4db8c0db2fa
Publikováno v:
Applied Sciences, Vol 9, Iss 20, p 4364 (2019)
Remote pulse rate measurement from facial video has gained particular attention over the last few years. Research exhibits significant advancements and demonstrates that common video cameras correspond to reliable devices that can be employed to meas
Externí odkaz:
https://doaj.org/article/b571a94114f44abf8e887b6e37010b25
Publikováno v:
Bio-Medical Materials and Engineering. :1-12
BACKGROUND: The COVID-19 pandemic has resulted in increased psychological pressure on mental health since 2019. The resulting anxiety and stress have permeated every aspect of life during confinement. OBJECTIVE: To provide psychologists with an unbia
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ae3196d3c9dea4ad274c02112b4537fe
https://doi.org/10.3233/bme-222542
https://doi.org/10.3233/bme-222542
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3a231254903032ba4ffac54fde87b713
https://doi.org/10.1109/cvprw56347.2022.00275
https://doi.org/10.1109/cvprw56347.2022.00275
Publikováno v:
IEEE Access, Vol 8, Pp 56992-57002 (2020)
Innovative technologies and naturalistic driving data sources provide a great potential to develop reliable autonomous driving systems. Understanding the behaviors of surrounding vehicles is essential for improving safety and mobility of autonomous v
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1ae8bae638f82c0485321e68c4300135
https://ieeexplore.ieee.org/document/9043491/
https://ieeexplore.ieee.org/document/9043491/
Publikováno v:
2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW).
We present in this paper the LCOMS Lab's approach to the 1st Vision For Vitals (V4V) Challenge organized within ICCV2021. The V4V challenge was focused on computer vision methods for vitals signs measurement from facial videos, including pulse rate (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1327d238f1e0054f16ede518e4d1bf81
https://doi.org/10.1109/iccvw54120.2021.00308
https://doi.org/10.1109/iccvw54120.2021.00308
Autor:
Frédéric Bousefsaf, Théo Desquins, Djamaleddine Djeldjli, Yassine Ouzar, Choubeila Maaoui, Alain Pruski
Publikováno v:
Biomedical Signal Processing and Control. 78:103895
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a5e2940e9050a9d6b15811c9c8017687
https://doi.org/10.1016/j.bspc.2022.103895
https://doi.org/10.1016/j.bspc.2022.103895
Publikováno v:
MED
In the context of autonomous driving, early identification and interpretation of surrounding vehicle’s maneuvers are key elements to ensure a high-level of road safety. In this paper, we present a new concept to classify and predict surrounding veh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4108139d2b657a6170de59e844512c94
https://doi.org/10.1109/med51440.2021.9480326
https://doi.org/10.1109/med51440.2021.9480326
Autor:
Alain Pruski, Choubeila Maaoui
Publikováno v:
Cutting Edge Robotics 2010
In this paper we presented an approach to emotion recognition based on the processing of physiological signals. Physiological data was acquired in six different affective states and two pattern recognition methods have been tested: SVM method and Fis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a8cc72cd5f6c02ba23ea57d0034b3c3
http://www.intechopen.com/articles/show/title/emotion-recognition-through-physiological-signals-for-human-machine-communication
http://www.intechopen.com/articles/show/title/emotion-recognition-through-physiological-signals-for-human-machine-communication
