Items where Author is "Al-Hiyali, M.I."

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Number of items: 9.

Sadiq, A. and Al-Hiyali, M.I. and Yahya, N. and Tang, T.B. and Khan, D.M. (2022) Non-Oscillatory Connectivity Approach for Classification of Autism Spectrum Disorder Subtypes Using Resting-State fMRI. IEEE Access, 10. pp. 14049-14061.

Al-Hiyali, M.I. and Yahya, N. and Faye, I. and Khan, Z. (2021) Autism Spectrum Disorder Detection Based on Wavelet Transform of BOLD fMRI Signals Using Pre-trained Convolution Neural Network. International Journal of Integrated Engineering, 13 (5). pp. 49-56.

Al-Hiyali, M.I. and Yahya, N. and Faye, I. and Khan, Z. (2021) Autism Spectrum Disorder Detection Based on Wavelet Transform of BOLD fMRI Signals Using Pre-trained Convolution Neural Network. International Journal of Integrated Engineering, 13 (5). pp. 49-56.

Al-Hiyali, M.I. and Yahya, N. and Faye, I. and Khan, Z. and Laboratoire, K.A. (2021) Classification of BOLD FMRI Signals using Wavelet Transform and Transfer Learning for Detection of Autism Spectrum Disorder. In: UNSPECIFIED.

Al-Hiyali, M.I. and Yahya, N. and Faye, I. and Khan, Z. and Laboratoire, K.A. (2021) Classification of BOLD FMRI Signals using Wavelet Transform and Transfer Learning for Detection of Autism Spectrum Disorder. In: UNSPECIFIED.

Al-Hiyali, M.I. and Yahya, N. and Faye, I. and Hussein, A.F. (2021) Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network. Sensors, 21 (16).

Al-Hiyali, M.I. and Yahya, N. and Faye, I. and Hussein, A.F. (2021) Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network. Sensors, 21 (16).

Khan, Z. and Yahya, N. and Alsaih, K. and Al-Hiyali, M.I. and Meriaudeau, F. (2021) Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review. IEEE Access, 9. pp. 97878-97905.

Khan, Z. and Yahya, N. and Alsaih, K. and Al-Hiyali, M.I. and Meriaudeau, F. (2021) Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review. IEEE Access, 9. pp. 97878-97905.

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