Items where Author is "Muzammel, M."

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Number of items: 9.

Article

Muzammel, M. and Yusoff, M.Z. and Saad, M.N.M. and Sheikh, F. and Awais, M.A. (2022) Blind-Spot Collision Detection System for Commercial Vehicles Using Multi Deep CNN Architecture. Sensors (Basel, Switzerland), 22 (16).

Shameen, Z. and Yusoff, M.Z. and Saad, M.N.M. and Malik, A.S. and Muzammel, M. (2018) Electroencephalography (EEG) based drowsiness detection for drivers: A review. ARPN Journal of Engineering and Applied Sciences, 13 (4). pp. 1458-1464.

Muzammel, M. and Yusoff, M.Z. and Meriaudeau, F. (2018) Event-Related Potential Responses of Motorcyclists Towards Rear End Collision Warning System. IEEE Access, 6. pp. 31609-31620.

Muzammel, M. and Yusoff, M.Z. and Meriaudeau, F. (2018) Event-Related Potential Responses of Motorcyclists Towards Rear End Collision Warning System. IEEE Access, 6. pp. 31609-31620.

Muzammel, M. and Yusoff, M.Z. and Malik, A.S. and Saad, M.N.M. and Meriaudeau, F. (2017) Motorcyclists safety system to avoid rear end collisions based on acoustic signatures. Proceedings of SPIE - The International Society for Optical Engineering, 10338.

Muzammel, M. and Yusoff, M.Z. and Meriaudeau, F. (2017) Rear-end vision-based collision detection system for motorcyclists. Journal of Electronic Imaging, 26 (3).

Muzammel, M. and Yusoff, M.Z. and Malik, A.S. and Saad, M.N.M. and Meriaudeau, F. (2017) Studying the response of drivers against different collision warning systems: A review. Proceedings of SPIE - The International Society for Optical Engineering, 10338.

Muzammel, M. and Yusoff, M.Y. and Saad, M.N.M. and Malik, A.S. (2016) Audio visual tracking of a speaker based on FFT and Kalman filter. ARPN Journal of Engineering and Applied Sciences, 11 (14). pp. 8947-8951.

Muzammel, M. and Yusoff, M.Y. and Saad, M.N.M. and Malik, A.S. (2016) Audio visual tracking of a speaker based on FFT and Kalman filter. ARPN Journal of Engineering and Applied Sciences, 11 (14). pp. 8947-8951.

This list was generated on Fri Nov 22 16:23:47 2024 +08.