Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Mounim El-Yacoubi"'
Autor:
Holger Fröhlich, Noémi Bontridder, Dijana Petrovska-Delacréta, Enrico Glaab, Felix Kluge, Mounim El Yacoubi, Mayca Marín Valero, Jean-Christophe Corvol, Bjoern Eskofier, Jean-Marc Van Gyseghem, Stepháne Lehericy, Jürgen Winkler, Jochen Klucken
Publikováno v:
Frontiers in Neurology, Vol 13 (2022)
Recent years have witnessed a strongly increasing interest in digital technology within medicine (sensor devices, specific smartphone apps) and specifically also neurology. Quantitative measures derived from digital technology could provide Digital B
Externí odkaz:
https://doaj.org/article/5bc8b5c20bbd4ab1a51849052901a6c5
Publikováno v:
Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications.
Publikováno v:
Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications.
Autor:
Hajar Hammouch, Sambit Mohapatra, Mounim El-Yacoubi, Huafeng Qin, Hassan Berbia, Patrick Mader, Mohamed Chikhaoui
Publikováno v:
2022 International Conference on Cyber-Physical Social Intelligence (ICCSI).
Autor:
Hajar Hammouch, Mounim El-Yacoubi, Huafeng Qin, Aissam Berrahou, Hassan Berbia, Mohamed Chikhaoui
Publikováno v:
2021 International Conference on Cyber-Physical Social Intelligence (ICCSI).
Publikováno v:
Transportation research. Part C, Emerging technologies
Transportation research. Part C, Emerging technologies, Elsevier, 2019, 101, pp.254-275. ⟨10.1016/j.trc.2019.02.013⟩
Transportation research. Part C, Emerging technologies, Elsevier, 2019, 101, pp.254-275. ⟨10.1016/j.trc.2019.02.013⟩
International audience; Fast urbanization generates increasing amounts of travel flows, urging the need for efficient transport planning policies. In parallel, mobile phone data have emerged as the largest mobility data source, but are not yet integr
Publikováno v:
Applied Intelligence
Applied Intelligence, Springer Verlag (Germany), 2019, 49 (6), pp.2218-2232. ⟨10.1007/s10489-018-1353-5⟩
Applied Intelligence, Springer Verlag (Germany), 2019, 49 (6), pp.2218-2232. ⟨10.1007/s10489-018-1353-5⟩
International audience; Hashing has been widely applied to approximate nearest neighbor search for large-scale multimedia retrieval. A variety of hashing methods have been developed for learning an efficient binary data representation, mainly by rela
This two-volume set constitutes the proceedings of the Third International Conference on Pattern Recognition and Artificial Intelligence, ICPRAI 2022, which took place in Paris, France, in June 2022. The 98 full papers presented were carefully review
Publikováno v:
BIBE 2019: 19th International Conference on Bioinformatics and Bioengineering
BIBE 2019: 19th International Conference on Bioinformatics and Bioengineering, Oct 2019, Athens, Greece. pp.258-264, ⟨10.1109/BIBE.2019.00053⟩
BIBE
BIBE 2019: 19th International Conference on Bioinformatics and Bioengineering, Oct 2019, Athens, Greece. pp.258-264, ⟨10.1109/BIBE.2019.00053⟩
BIBE
International audience; This paper presents the Derivatives Combination Predictor (DCP), a novel model fusion algorithm for making long-term glucose predictions for diabetic people. First, using the history of glucose predictions made by several mode
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::badd046e9384d211dd9f64c5439ad750
https://hal.archives-ouvertes.fr/hal-02481403
https://hal.archives-ouvertes.fr/hal-02481403
Publikováno v:
ECML PKDD 2018: Machine Learning and Knowledge Discovery in Databases
ECML PKDD 2018: Machine Learning and Knowledge Discovery in Databases, Sep 2018, Dublin, Ireland. pp.569-584, ⟨10.1007/978-3-030-10997-4_35⟩
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030109967
ECML/PKDD (3)
ECML PKDD 2018: Machine Learning and Knowledge Discovery in Databases, Sep 2018, Dublin, Ireland. pp.569-584, ⟨10.1007/978-3-030-10997-4_35⟩
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030109967
ECML/PKDD (3)
International audience; Large-scale and real-time transport mode detection is an open challenge for smart transport research. Although massive mobility data is collected from smartphones, mining mobile network geolocation is non-trivial as it is a sp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7fedef071a7e98480170e1bc66ffb3df
https://hal.archives-ouvertes.fr/hal-01939608/document
https://hal.archives-ouvertes.fr/hal-01939608/document