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Axe(s) de recherche : Systèmes intelligents communiquants
Domaine(s) de compétence :
Informatique, Génie logiciel, systémes d'informations, bases de données
Ingénieur d’Etat en génie Informatique
BiographiePas de biographie pour le moment.
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Publications de Abdallah MOUJAHID
« Safe Driving Mechanism: Detection, Recognition and Avoidance of Road Obstacles »par Abdallah MOUJAHID, Manolo HINA et Assia SOUKANE
KEOD 2018, 10th International Conference on Knowledge Engineering and Ontology Development , 18-20 September 2018, Seville, Espagne , 2018
Liste des auteurs : Andrea Ortalda, Abdallah Moujahid, Manolo Dulva Hina, Assia Soukane, Amar Ramdane-Cherif
In an intelligent vehicle (autonomous or semi-autonomous), detection and recognition of road obstacle is very important for it is the failure to recognize an obstacle on time which is the primary reason for road vehicular accidents that very often leads to human fatalities. In the intelligent vehicle of the future, safe driving is a primary consideration. This is accomplished by integrating features what will assist drivers in times of needs, one of which is avoidance of obstacle. In this paper, our knowledge engineering is focused on the detection, classification and avoidance of road obstacles. Ontology and formal specifications are used to describe such mechanism. Different supervised learning algorithms are used to recognize and classify obstacles. The avoidance of obstacles is implemented using reinforcement learning. This work is a contribution to the ongoing research in safe driving, and a specific application of the use of machine learning to prevent road accidents.
« Machine Learning Techniques in ADAS: A Review »par Abdallah MOUJAHID, Manolo HINA et Assia SOUKANE
ICACCE 2018, 4th IEEE International Conference on Advances in Computing & Communication Engineering , 22-23 June 2018, Paris, France , 2018
Liste des auteurs : Abdallah Moujahid, Manolo Dulva Hina, Assia Soukane, Mounir El Araki Tantaoui, Ahmed El Khadimi, Andrea Ortalda, Amar Ramdane-Cherif
What machine learning (ML) technique is used for system intelligence implementation in ADAS (advanced driving assistance system)? This paper tries to answer this question. This paper analyzes ADAS and ML independently and then relate which ML technique is applicable to what ADAS component and why. The paper gives a good grasp of the current state-of-the-art. Sample works in supervised, unsupervised, deep and reinforcement learnings are presented; their strengths and rooms for improvements are also discussed. This forms part of the basics in understanding autonomous vehicle. This work is a contribution to the ongoing research in ML aimed at reducing road traffic accidents and fatalities, and the invocation of safe driving.