Alsulaiman, Mansour

Deep Learning for EEG motor imagery classification based on multi-layer CNNs feature fusion

Amin, S. U., Alsulaiman, M., Muhammad, G., Mekhtiche, M. A., & Shamim Hossain, M. (2019) · Future Generation Computer Systems

EEG and Brain-Computer InterfacesEmotion and Mood Recognition

Cited by 523

A comprehensive survey on multimodal medical signals fusion for smart healthcare systems

Muhammad, G., Alshehri, F., Karray, F., Saddik, A. E., Alsulaiman, M., & Falk, T. H. (2021) · Information Fusion

Non-Invasive Vital Sign MonitoringAdvanced Image Fusion Techniques

Cited by 287

Voice Pathology Detection and Classification Using Auto-Correlation and Entropy Features in Different Frequency Regions

Al-Nasheri, A., Muhammad, G., Alsulaiman, M., Ali, Z., Malki, K. H., Mesallam, T. A., & Farahat Ibrahim, M. (2018) · IEEE Access

Voice and Speech DisordersPhonocardiography and Auscultation Techniques

Cited by 174

Multidirectional Regression (MDR)-Based Features for Automatic Voice Disorder Detection

Muhammad, G., Mesallam, T. A., Malki, K. H., Farahat, M., Mahmood, A., & Alsulaiman, M. (2012) · Journal of Voice

Voice and Speech DisordersSpeech Recognition and Synthesis

Cited by 66

Automatic Voice Pathology Detection With Running Speech by Using Estimation of Auditory Spectrum and Cepstral Coefficients Based on the All-Pole Model

Ali, Z., Elamvazuthi, I., Alsulaiman, M., & Muhammad, G. (2016) · Journal of Voice

Voice and Speech DisordersSpeech and Audio Processing

Cited by 59