Constellation, le dépôt institutionnel de l'Université du Québec à Chicoutimi

Article publié dans une revue avec comité d'évaluation

Chehri, Hamou, Chehri, Abdellah et Hakem, Nadir. (2019). In underground vehicular radio channel characterization. Procedia Computer Science, 159, p. 514-523.

Chehri, Hamou, Chehri, Abdellah, Kiss, László et Zimmerman, Alfred. (2020). Automatic anode rod inspection in aluminum smelters using deep-learning techniques: a case study. Procedia Computer Science, 176, p. 3536-3544.

Chapitre de livre

Chehri, Hamou, Chehri, Abdellah et Saadane, Rachid. (2021). Traffic Signs Detection and Recognition System in Snowy Environment Using Deep Learning. Dans Innovations in Smart Cities Applications Volume 4. (183, p. 503-513). Lecture Notes in Networks and Systems book series (LNNS, volume 183). Cham : Springer.

Matériel de conférence

Chehri, Abdellah, Chehri, Hamou, Hakim, Nadir et Saadane, Rachid. (2020). Realistic 5.9 GHz DSRC vehicle-to-vehicle wireless communication protocols for cooperative collision warning in underground mining. Dans : Proceedings of 3rd KES-STS International Symposium, Smart Transportation Systems 2020, Smart Innovation, Systems and Technologies book series (SIST, volume 185) , 17-19 June 2020, Virtual Conference Centre.

Chehri, Hamou, Chehri, Abdellah et Hakem, Nadir. (2019). Empirical radio channel characterization at 5.9 GHz for vehicle-to-infrastructure communication. Dans : 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall) , 22-25 Sept. 2019, Honolulu, HI, USA.

Chehri, Hamou, Chehri, Abdellah et Saadane, Rachid. (2020). Traffic Signs Detection and Recognition System in Snowy Environment Using Deep Learning. Dans : The Proceedings of the Third International Conference on Smart City Applications, SCA 2020: Innovations in Smart Cities Applications Volume 4 , 7-9 october, 2020, Karabuk, Turkey.