Výsledky vyhledávání - "Soufiane HAMIDA"

Akademický článek

Early heart disease prediction using feature engineering and machine learning algorithms

Autor: Mohammed Amine Bouqentar, Oumaima Terrada, Soufiane Hamida, Shawki Saleh, Driss Lamrani, Bouchaib Cherradi, Abdelhadi Raihani

Publikováno v: Heliyon, Vol 10, Iss 19, Pp e38731- (2024)

Heart disease is one of the most widespread global health issues, it is the reason behind around 32 % of deaths worldwide every year. The early prediction and diagnosis of heart diseases are critical for effective treatment and sickness management. D

Externí odkaz: https://doaj.org/article/a80eba87a89e4fd2bf44585373026ae2

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Efficient feature descriptor selection for improved Arabic handwritten words recognition

Autor: Soufiane Hamida, Oussama El Gannour, Bouchaib Cherradi, Hassan Ouajji, Abdelhadi Raihani

Arabic handwritten text recognition has long been a difficult subject, owing to the similarity of its characters and the wide range of writing styles. However, due to the intricacy of Arabic handwriting morphology, solving the challenge of cursive ha

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bcf21d8d6e071833f9527e59d6563511
https://zenodo.org/record/7069452

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Classifying toxicity in the Arabic Moroccan dialect on Instagram: a machine and deep learning approach

Autor: Rabia Rachidi, Mohamed Amine Ouassil, Mouaad Errami, Bouchaib Cherradi, Soufiane Hamida, Hassan Silkan

Publikováno v: Indonesian Journal of Electrical Engineering and Computer Science. 31:588

People crave interaction and connection with other people. Therefore, social media became the center of society’s life. Among the brightest social media platforms nowadays with a massive number of daily users there is Instagram, which is due to its

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c373ca4acb974a1931c71378096e7666
https://doi.org/10.11591/ijeecs.v31.i1.pp588-598

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Evaluating multi-state systems reliability with a new improved method

Autor: Yasser Lamalem, Oussama EL GANNOUR, Yassine Tazouti, Bouchaib CHERRADI, Soufiane HAMIDA, Khalid Housni

The computation of network reliability for a system with many states is an NP-hard issue. Finding all the minimum path vectors (d-MPs) lower boundary points for each level d is one of the few approaches for computing such dependability. This research

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68e3448da213f0574907f99338b64aef
https://zenodo.org/record/6781693

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