Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Hakim Hafidi"'
Publikováno v:
IEEE Access, Vol 11, Pp 23989-24002 (2023)
Many datasets can be represented by attributed graphs on which classification methods may be of interest. The problem of node classification has attracted the attention of scholars due to its wide range of applications. The problem consists of predic
Externí odkaz:
https://doaj.org/article/f60ff0f015164a0e8770844679ffd5c5
Autor:
Chaimae Asaad, Bassma Guermah, Mounir Ghogho, Hakim Hafidi, Abdelghani Ghanem, Mehdi Zakroum, Nada Sbihi, Karim Baïna, Youness Moukafih, Mariam Cherqaoui, Meriem Dairi
Publikováno v:
International Journal of Environmental Research and Public Health
Volume 18
Issue 22
International Journal of Environmental Research and Public Health, Vol 18, Iss 12172, p 12172 (2021)
Volume 18
Issue 22
International Journal of Environmental Research and Public Health, Vol 18, Iss 12172, p 12172 (2021)
The impact of COVID-19 on socio-economic fronts, public health related aspects and human interactions is undeniable. Amidst the social distancing protocols and the stay-at-home regulations imposed in several countries, citizens took to social media t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d2c2fe867f4117cf970c26e9bd200ab6
Publikováno v:
IEEE Statistical Signal Processing Workshop (SSP)
IEEE Statistical Signal Processing Workshop (SSP), 2021, Rio de Janeiro (virtual), Brazil
SSP
IEEE Statistical Signal Processing Workshop (SSP), 2021, Rio de Janeiro (virtual), Brazil
SSP
International audience; Graph neural networks (GNN) have been recognized as powerful tools for learning representations in graph structured data. The key idea is to propagate and aggregate information along edges of the given graph. However, little w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c220628c2a9c33e11daa9255b65f3b92
https://hal.archives-ouvertes.fr/hal-03291075
https://hal.archives-ouvertes.fr/hal-03291075
Publikováno v:
Signal Processing. 190:108310
Contrastive learning has become a successful approach for learning powerful text and image representations in a self-supervised manner. Contrastive frameworks learn to distinguish between representations coming from augmentations of the same data poi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2152c2610fcd36b69211db06cc1bfe59
https://doi.org/10.1016/j.sigpro.2021.108310
https://doi.org/10.1016/j.sigpro.2021.108310
Publikováno v:
INISTA
Driver aggressiveness is a major cause of traffic accidents. Aggressive driving detection is an important application in the field of intelligent transportation systems (ITS). Developing systems capable of automatically detecting aggressive driving b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1f4fc47892a7944beeb8f92ab5e8ba03
https://doi.org/10.1109/inista.2019.8778416
https://doi.org/10.1109/inista.2019.8778416