Mustafa Zuhaer Nayef Al-Dabagh
Asst. Lec , PhD
Email: [email protected]
القسم : علوم حاسبات
Dr. Mustafa Zuhaer Nayef Al-Dabagh holds a Bachelor of Engineering (B.Eng.) in Computer Technology Engineering and a Master of Technology (M.Tech.) in Computer Engineering Technology from Northern Technical University. He earned his Doctor of Philosophy (PhD) in Computer Engineering from Universiti Malaysia Perlis (UniMAP), specializing in feature fusion techniques for face recognition and advanced local feature extraction methods.
With expertise in combining theoretical foundations with practical applications, Dr. Al-Dabagh is passionate about advancing research and education in computer science and engineering. He is committed to contributing innovative solutions to contemporary challenges in the field while fostering a deeper understanding of computer science principles among students and researchers alike
- Arora, Nitin, Anupam Singh, Mustafa Zuhaer Nayef Al-Dabagh, and Sumit Kumar Maitra. "A Novel Architecture for Diabetes Patients’ Prediction Using K-Means Clustering and SVM." Mathematical Problems in Engineering 2022 (2022). doi: 10.1155/2022/4815521
- Congru Liu, Mingsen Lin, Kayhan Zrar Ghafoor, Mustafa Zuhaer Nayef Al-Dabagh and Dimitrios A. Karras. “Optimization of Building Construction Control System Based on Nonlinear Image Enhancement”."Computer-Aided Design and Applications". pp. 213-224. doi: 10.14733/cadaps.2023.S2.213-224.
- M. Z. Nayef Al-Dabagh, M. I. Ahmad and S. A. Anwar, "Face Recognition Based on Fusion of Multiple Masks Local Feature Sets Using Wavelet Transform," 2021 6th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE), 2021, pp. 1-6, doi: 10.1109/ICRAIE52900.2021.9703718.
- Mohammed, M. Z. N. Al-Dabagh, S. J. Rashid, and N. A. M. Isa, “Path discovering in maze area using mobile robot,” TELKOMNIKA Telecommun. Comput. Electron. Control, vol. 20, no. 2, pp. 416–425, 2022, doi: 10.12928/TELKOMNIKA.v20i2.19408.
- M. Z. N. Al-Dabagh and M. I. Ahmad, “Face Recognition System Using Local Features Fusion for Multi-Masks,” J. Phys. Conf. Ser., vol. 2107, no. 1, p. 12044, Nov. 2021, doi: 10.1088/1742-6596/2107/1/012044.
- N. A. A. Khalid, M. I. Ahmad, T. H. Mandeel, M. N. M. Isa, R. A. R. Ahmad, and M. Z. N. Al-Dabagh, “Palmprint {ROI} Cropping Based on Enhanced Correlation Coefficient Maximisation Algorithm,” in 2021 {IEEE} 11th International Conference on System Engineering and Technology ({ICSET}), Nov. 2021, doi: 10.1109/icset53708.2021.9612436.
- M. Al-Dabagh, “Motion artifacts reduction in cardiac pulse signal acquired from video imaging,” Int. J. Electr. Comput. Eng., 2020.
- M. Al-Dabagh, “Face Recognition System Based on Fusion Features of Local Methods Using CCA,” in 2020 8th International Electrical Engineering Congress (iEECON), 2020, doi: 10.1109/ieecon48109.2020.229489.
- M. Al-Dabagh, “Exploiting Wavelet Transform, Principal Component Analysis, Support Vector Machine, and K-Nearest Neighbors for Partial Face Recognition,” Cihan Univ. Sci. J., 2019, doi: 10.24086/cuesj.v3n2y2019.pp80-84.
- D. Abdullah, M. Al-Dabagh, and M. Alhabib, “Independent Component Analysis and Support Vector Neural Network for Face Recognition,” Int. J. Appl. Eng. Res., vol. 13, 2018.
- M. Al-Dabagh, “Intelligent surveillance robot,” in 2013 International Conference on Electrical Communication, Computer, Power, and Control Engineering (ICECCPCE), 2014, doi: 10.1109/ICECCPCE.2013.6998745.
- M. Al-Dabagh, “Face Recognition Using LBP, FLD and SVM with Single Training Sample Per Person,” Int. J. Sci. & Eng. Res., 2014.
- Mustafa Zuhaer Nayef Al-Dabagh, “Security Robot System for Intelligent Building”, LAMBERT Academic Publishing, 2014.
- M. Al-Dabagh, “Improvement of Face Recognition System Based on Linear Discrimination Analysis and Support Vector Machine,” Eng. Technol. J., vol. 31, pp. 2261–2272, 2013.
- T. Salih and M. Al-Dabagh, “New Design of Mobile Robot Path Planning with Randomly Moving Obstacles,” J. Eng. Sci., vol. 20, pp. 21–28, 2013.
- T. Salih and M. Al-Dabagh, “Face Recognition System based on Wavelet, PCA-LDA and SVM,” Comput. Eng. Intell. Syst., vol. 4, pp. 26–31, 2013.
- N. A. Othman, “A New Embedded Surveillance System for Reducing COVID-19 Outbreak in Elderly Based on Deep Learning and IoT.”
- I. M. Mohammed, M. Z. N. Al-Dabagh, M. I. Ahmad, and M. N. M. Isa, “Face Recognition Using PCA Implemented on Raspberry Pi,” in Proceedings of the 11th National Technical Seminar on Unmanned System Technology 2019, 2021, pp. 873–889.
- I. S. Mohsin, M. I. Ahmad, S. M. Salman, M. Z. N. Al-Dabagh, M. N. M. Isa, and R. A. R. Ahmad, “DCT Image Compression Implemented on Raspberry Pi to Compress Image Captured by CMOS Image Sensor,” Lect. Notes Electr. Eng., vol. 666, pp. 831–841, 2020, doi: 10.1007/978-981-15-5281-6_60.
- D. F. AL-Mukhtar and M. Z. N. AL-Dabagh, “Real-Time Face Recognition System Using KPCA, LBP and Support Vector Machine,” Int. J. Adv. Eng. Res. Sci., vol. 4, no. 2, pp. 184–189, 2017, doi: 10.22161/ijaers.4.2.36.
- M. Z. AL-Dabagh and D. F. H. AL-Mukhtar, “Breast Cancer Diagnostic System Based on MR images Using KPCA-Wavelet Transform and Support Vector Machine,” Int. J. Adv. Eng. Res. Sci., vol. 4, no. 3, pp. 258–263, 2017, doi: 10.22161/ijaers.4.3.41.
- M. Z. Al-Dabagh, M. H. Mohammed Alhabib, and F. H. AL-Mukhtar, “Face Recognition System Based on Kernel Discriminant Analysis, K-Nearest Neighbor and Support Vector Machine,” Int. J. Res. Eng., 2018, doi: 10.21276/ijre.2018.5.3.3.
- M. Al-Yoonus, A. A. Yaseen, and M. Z. N. Al-Dabagh, “Deformation Detection and Classification system for Car parts Products Using Image Processing Algorithms,” in IOP Conference Series: Materials Science and Engineering, 2019, vol. 518, no. 4, doi: 10.1088/1757-899X/518/4/042006.
- Digital Image Processing
- Computer Graphics
- Discrete Mathematics
- Programming Fundamentals
- Computer Networks
- Operating Systems
- Logic Design
- Computer Skills
- Computer Architecture
- Database System
• Design and analysis the hand geometry identification, (Project), 2008.