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Muhammad Muzammel
Muhammad Muzammel
Verified email at u-pec.fr
Title
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Cited by
Year
EEG based Major Depressive disorder and Bipolar disorder detection using Neural Networks: A review
S Yasin, SA Hussain, S Aslan, I Raza, M Muzammel, A Othmani
Computer Methods and Programs in Biomedicine 202, 106007, 2021
1002021
AudVowelConsNet: A phoneme-level based deep CNN architecture for clinical depression diagnosis
M Muzammel, H Salam, Y Hoffmann, M Chetouani, A Othmani
Machine Learning with Applications 2, 100005, 2020
582020
End-to-end multimodal clinical depression recognition using deep neural networks: A comparative analysis
M Muzammel, H Salam, A Othmani
Computer Methods and Programs in Biomedicine 211, 106433, 2021
452021
A model of normality inspired deep learning framework for depression relapse prediction using audiovisual data
A Othmani, AO Zeghina, M Muzammel
Computer Methods and Programs in Biomedicine 226, 107132, 2022
182022
Enhancing EEG signals in brain computer interface using intrinsic time-scale decomposition
EA Mohamed, MZ Yusoff, IK Adam, EA Hamid, F Al-Shargie, M Muzammel
Journal of Physics: Conference Series 1123 (1), 012004, 2018
182018
Identification of signs of depression relapse using audio-visual cues: A preliminary study
M Muzammel, A Othmani, H Mukherjee, H Salam
2021 IEEE 34th International Symposium on Computer-Based Medical Systems …, 2021
142021
Rear-end vision-based collision detection system for motorcyclists
M Muzammel, MZ Yusoff, F Meriaudeau
Journal of Electronic Imaging 26 (3), 033002-033002, 2017
112017
Event-related potential responses of motorcyclists towards rear end collision warning system
M Muzammel, MZ Yusoff, F Meriaudeau
Ieee Access 6, 31609-31620, 2018
102018
Electroencephalography (EEG) based drowsiness detection for drivers: A review
Z Shameen, MZ Yusoff, MNM Saad, AS Malik, M Muzammel
ARPN Journal of Engineering and Applied Sciences 13 (4), 2018
72018
Blind-Spot Collision Detection System for Commercial Vehicles Using Multi Deep CNN Architecture
M Muzammel, MZ Yusoff, MNM Saad, F Sheikh, MA Awais
Sensors 22 (16), 6088, 2022
52022
Motorcyclists safety system to avoid rear end collisions based on acoustic signatures
M Muzammel, MZ Yusoff, AS Malik, MNM Saad, F Meriaudeau
Thirteenth International Conference on Quality Control by Artificial Vision …, 2017
32017
Studying the response of drivers against different collision warning systems: A review
M Muzammel, MZ Yusoff, AS Malik, MNM Saad, F Meriaudeau
Thirteenth International Conference on Quality Control by Artificial Vision …, 2017
22017
An Ambient Intelligence-Based Approach for Longitudinal Monitoring of Verbal and Vocal Depression Symptoms
A Othmani, M Muzammel
International Workshop on PRedictive Intelligence In MEdicine, 206-217, 2023
2023
PROCEDE POUR DETERMINER LE NIVEAU DE POLLUTIONDANS LE SOUS-SOL D’UN SITE
A Othmani, A Triger, M Muzammel, T Westelynck
2022
One-Shot Learning Approach for Depression Relapse Detection using Audio-visual Cues
M Muzammel, A Othmani, AO Zeghina, H Salam
Pattern Recognition Letters, 2021
2021
Neural Networks based approaches for Major Depressive Disorder and Bipolar Disorder Diagnosis using EEG signals: A review
S Yasina, SA Hussaina, S Aslanc, I Razaa, M Muzammele, A Othmanie
arXiv preprint arXiv:2009.13402, 2020
2020
Visual and acoustic techniques for motorcycle collision warning system with EEG validation
M Muzammel
Université Bourgogne Franche-Comté; Universiti Teknologi Malaysia, 2018
2018
Développement d'un système d'avertissemment sonore, validé par EEG, basé sur des approches vision et acoustique pour la detection de véhicules approchants des véhicules moteur …
M Muzammel
Bourgogne Franche-Comté, 2018
2018
Visual and Acoustic based Techniques for Motorcycle Collision Warning System with EEG Validation
M MUZAMMEL
Universiti Teknologi PETRONAS, 2018
2018
AUDIO VISUAL TRACKING OF A SPEAKER BASED ON FFT AND KALMAN FILTER
M Muzammel, MZ Yusoff, MNM Saad, AS Malik
ARPN Journal of Engineering and Applied Sciences 6, 8947-8951, 2016
2016
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