Khaled T. Wassif
Professor of Computer Science, Faculty of Computers and Artificial Intelligence, Cairo University
5 Dr. Ahmed Zewail Street, Postal Code: 12613, Cairo Univ. Post Office, Giza, Egypt
(email)
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2024
Ali, I., K. Wassif, and H. Bayomi,
"
Improve the efficiency of network traffic in IoT using dimensionality reduction
",
2024 6th International Conference on Computing and Informatics (ICCI)
, 2024.
Faheem, M. A., K. T. Wassif, H. Bayomi, and S. M. Abdou,
"
Improving neural machine translation for low resource languages through non-parallel corpora: a case study of Egyptian dialect to modern standard Arabic translation
",
Scientific Reports
, vol. 14, issue 1, pp. 2265, 2024.
2023
Warad, A. A. M.;, K.; Wassif, and N. R.; Darwish,
"
Intelligent models for forecasting repair timing of leakage water pipelines
",
2023 International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC)
, 2023.
2022
Al-Boghdady, A.;, M.; El-Ramly, and K.; Wassif,
"
iDetect for vulnerability detection in internet of things operating systems using machine learning
",
Scientific Reports
, vol. 12, issue 1, pp. 17086, 2022.
2015
El_Hawy, M., H. Hassan, H. Hefny, and K. Wassif,
"
An Improved Fuzzy Number Approximation using Shadowed Sets
",
International Journal of Computer Applications (IJCA)
, vol. 118, issue 25, pp. 503-509, 2015.
2004
Ali Fahmy, S. A. M., S. El-Gammal, K. Wassif, and I. Amr,
"
Integrating Interest-Driven and Data-Driven Discovery for Medical Quality Management
",
The Second International Conference on Informatics and Systems (INFOS2004)
, March-6-8, 2004.
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Recent Publications
Assessment Software Reliability in Component-Based Software Systems: A Comprehensive Review
Improve the efficiency of network traffic in IoT using dimensionality reduction
An ensemble learning model for forecasting water-pipe leakage
Improving neural machine translation for low resource languages through non-parallel corpora: a case study of Egyptian dialect to modern standard Arabic translation
Dimensionality reduction for images of IoT using machine learning
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