Takip et
Université Hassan 2 - faculté des sciences ain chock de Casablanca
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Alıntı yapanlar
Alıntı yapanlar
The detection of Parkinson disease using the genetic algorithm and SVM classifier
Z Soumaya, BD Taoufiq, N Benayad, K Yunus, A Abdelkrim
Applied Acoustics 171, 107528, 2021
Diagnosis of Parkinson’s Disease based on Wavelet Transform and Mel Frequency Cepstral Coefficients
Taoufiq BELHOUSSINE DRISSI, S Zayrit, B Nsiri, A Ammoummou
International Journal of Advanced Computer Science and Applications 10 (3), 2019
A hybrid method for the diagnosis and classifying parkinson's patients based on time–frequency domain properties and K-nearest neighbor
Z Soumaya, BD Taoufiq, N Benayad, B Achraf, A Ammoumou
Journal of Medical Signals & Sensors 10 (1), 60-66, 2020
Diagnosis of Parkinson disease using the wavelet transform and MFCC and SVM classifier
Z Soumaya, BD Taoufiq, B Nsiri, A Abdelkrim
2019 4th World Conference on Complex Systems (WCCS), 1-6, 2019
ECG signal diagnosis using Discrete Wavelet Transform and K-Nearest Neighbor classifier
nsiri benayad toulni youssef, belhoussine drissi taoufiq
The 4th International Conference on Networking, Information Systems & Security, 2021
Electrocardiogram signals classification using discrete wavelet transform and support vector machine classifier
Y Toulni, N Benayad, BD Taoufiq
Int J Artif Intell ISSN 2252 (8938), 8938, 2021
An intelligent approach based on the combination of the discrete wavelet transform, delta delta MFCC for Parkinson's disease diagnosis
B Nouhaila, BD Taoufiq, N Benayad
International Journal of Advanced Computer Science and Applications 13 (4), 2022
Features selection by genetic algorithm optimization with k-nearest neighbour and learning ensemble to predict Parkinson disease
N Benayad, Z Soumaya, BD Taoufiq, A Abdelkrim
Int. J. Electr. Comput. Eng.(2088-8708) 12, 1982-1989, 2022
Daubechies Wavelet Cepstral Coefficients for Parkinson’s Disease Detection
S Zayrit, BD Taoufiq, A Ammoumou, B Nsiri
complex systems 29 (3), 729-739, 2020
CNN and LSTM for the classification of parkinson's disease based on the GTCC and MFCC
N Boualoulou, TB Drissi, B Nsiri
Applied Computer Science 19 (2), 1-24, 2023
Speech analysis for the detection of Parkinson’s disease by combined use of empirical mode decomposition, Mel frequency cepstral coefficients, and the K-nearest neighbor classifier
N Boualoulou, B Nsiri, TB Drissi, S Zayrit
ITM Web of Conferences 43, 01019, 2022
ECG Signal Classification Using DWT, MFCC and SVM Classifier
Y Toulni, B Nsiri, TB Drissi
Traitement du Signal 40 (1), 335, 2023
Cepstral Coefficient Extraction using the MFCC with the Discrete Wavelet Transform for the Parkinson’s Disease Diagnosis
BD Taoufiq, Z Soumaya, N Benayad, B Nouhaila
International Journal of Engineering Trends and Technology 70 (7), 283-290, 2022
A novel Parkinson's disease detection algorithm combined EMD, BFCC, and SVM classifier
N Boualoulou, M Mounia, B Nsiri, T Behoussine Drissi
Diagnostyka 24, 2023
Predicting Parkinson's disease based on transformed speech signal by DWT with two methods for features selection: GA-AdaBoost and BPSO
Z Soumaya, N Benayad, BD Taoufiq, A Abdelkrim
2022 7th International Conference on Mathematics and Computers in Sciences …, 2022
Direct Torque Control for Induction Motor
MA Isha, A Ouchatti, TB Drissi
2021 International Conference on Digital Age & Technological Advances for …, 2021
Study of the Transmission of Ultrasonic Guided Wave at the Junction of Two Different Elastic Plates with the Presence of a Defect
T Belhoussine Drissi, B Morvan, M Predoi, JL Izbicki, P Pareige
Key Engineering Materials 482, 21-29, 2011
Use of ANN, LSTM and CNN Classifiers for the New MSCC and BSCC Methods in the Detection of Parkinson's Disease by Voice Analysis.
M Mounia, B Nouhaila, N Benayad, BD Taoufiq
International Journal of Advanced Computer Science & Applications 14 (12), 2023
Voice-Based Detection of Parkinson’s Disease Using Empirical Mode Decomposition, IMFCC, MFCC, and Deep Learning
N Boualoulou, M Miyara, B Nsiri, TB Drissi
The International Conference on Artificial Intelligence and Smart …, 2023
DWT-BSS: Blind Source Separation applied to EEG signals by extracting wavelet transform’s approximation coefficients
H Massar, B Nsiri, TB Drissi
Journal of Physics: Conference Series 2550 (1), 012031, 2023
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