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Duhayyim, M. A., T. A. E. Eisa, F. N. Al-Wesabi, A. Abdelmaboud, M. A. Hamza, A. S. Zamani, M. Rizwanullah, and R. Marzouk, "Deep Reinforcement Learning Enabled Smart City Recycling Waste Object Classification", Computers, Materials & Continua, vol. 71, issue 3, pp. 5699-5715, 2022.
Mohammed, A., and et al, "Deep Reinforcement Learning Approach for Augmented Reality Games", International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC 2021). In press ( IEEE Xplorer), 26 May, 2021.
Leheta, T. M., R. M. Abdel Hay, and Y. F. El Garem, "Deep peeling using phenol versus percutaneous collagen induction combined with trichloroacetic acid 20% in atrophic post-acne scars; a randomized controlled trial", Journal of Dermatological Treatment, vol. 25, no. 2: Informa Healthcare USA on behalf of Informa UK Ltd. London, pp. 130–136, 2014. Abstract

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Leheta, T. M., R. M. A. B. D. E. L. HAY, and Y. F. El Garem, "Deep peeling using phenol versus percutaneous collagen induction combined with trichloroacetic acid 20% in atrophic post-acne scars; a randomized controlled trial", Journal of Dermatological Treatment, vol. 25, no. 2: Taylor & Francis, pp. 130–136, 2014. Abstract
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El-Dawlatly, M. M., M. S. M. Fayed, and Y. A. Mostafa, Deep overbite malocclusion: Analysis of the underlying components., , 2012.
Youssef, A., M. A. Abdel-Fattah, A. O. Touny, Z. K. Hassan, A. Nassar, M. M. Lotfy, A. Moustafa, M. M. Eldin, A. Bahnassy, and A. - R. N. Zekri, Deep Next Generation Sequencing Identifies Somatic Mutational Signature in Egyptian Colorectal Cancer Patients, , 2020. Abstract
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, "A deep neural network for simultaneous estimation of b jet energy and resolution", Computing and software for big science, vol. 4, no. 1: Springer, pp. 1–20, 2020. Abstract
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, "The deep lymphatic system of the lower limb in filarial lymphoedema", The Egyptian Journal of Surgery, vol. 4, pp. 11-15, 1985.
Shafi, M., R. H. Mari, A. Khatab, M. Henini, A. Polimeni, M. Capizzi, and M. Hopkinson, "Deep levels in H-irradiated GaAs1-xNx (x< 0.01) grown by molecular beam epitaxy", Journal of Applied Physics, vol. 110, no. 12: AIP Publishing, pp. 124508, 2011. Abstract
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Shafi, M., R. H. Mari, A. Khatab, M. Henini, A. Polimeni, M. Capizzi, and M. Hopkinson, "Deep levels in H-irradiated GaAs1-xNx (x< 0.01) grown by molecular beam epitaxy", Journal of Applied Physics, vol. 110, no. 12: AIP Publishing, pp. 124508, 2011. Abstract
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Taha, M. H. N., G. Manogaran, M. H. N. Taha, and M. Loey, "A deep learning semantic segmentation architecture for COVID‐19 lesions discovery in limited chest CT datasets", Expert Systems, vol. 39, issue 6, 2022.
Yosri, A., M. Ghaith, and W. El-Dakhakhni, "Deep learning rapid flood risk predictions for climate resilience planning", Journal of Hydrology, vol. March 2024, pp. 130817, 2024.
Marzouk, M., N. Elshaboury, A. Abdel-Latif, and S. Azab, "Deep Learning Model for Forecasting COVID-19 Outbreak in Egypt", Process Safety and Environmental Protection, vol. 153, pp. 363-375, 2021.
Abd El-Aziz, A. A., N. A. Azim, M. A. Mahmood, and H. Alshammari, "A Deep Learning Model for Face Mask Detection", IJCSNS International Journal of Computer Science and Network Security, vol. 21, issue 10, pp. 101--106, 2021.
El-Aziz, A. A. A., N. A. Azim, M. A. Mahmood, and H. Alshammari, "A Deep Learning Model for Face Mask Detection ", IJCSNS, vol. 21, issue 10, pp. 101-106, 2021.
Abd El-Aziz, A. A., N. A. Azim, M. A. Mahmood, and H. Alshammari, "A Deep Learning Model for Face Mask Detection", IJCSNS International Journal of Computer Science and Network Security, vol. 21, no. 10, pp. 101–106, 2021. Abstract
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Gabr, R. H., A. I. Shahin, A. A. Sharawi, and M. A. AOUF, "A DEEP LEARNING IDENTIFICATION SYSTEM FOR DIFFERENT EPILEPTIC SEIZURE DISEASE STAGES", JOURNAL OF ENGINEERING AND APPLIED SCIENCE, vol. 67, issue 4, pp. 925-944, 2020.
Rashwan, M. A. A., A. A. A. Sallab, H. M. Raafat, and A. Rafea, "Deep learning framework with confused sub-set resolution architecture for automatic Arabic diacritization", IEEE Transactions on Audio, Speech, and Language Processing, vol. 23, issue 2329-9290, pp. 505-516, 2015. deep_learning_framework_with_confused_sub-set.pdf
El-Sayed, O. A., S. K. Fawzy, S. H. Tolba, R. S. Salem, Y. S. Hassan, A. M. Ahmed, and A. Khattab, "Deep Learning Framework for Accurate Network Intrusion Detection in ITSs", IEEE International Conference on Microelectronics (ICM), Egypt, IEEE, 2021.
Abdelhay, M., A. Mohammed, and H. A. Hefny, "Deep learning for Arabic healthcare: MedicalBot", Social Network Analysis and Mining, vol. 13, pp. 2-17, 2023.
Atef, M., A. Khattab, E. A. Agamy, and M. M. Khairy, "Deep Learning Based Time-Series Forecasting Framework for Olive Precision Farming", IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), Lansing, MI, USA, IEEE, 2021.
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