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كل ما تحتاجه من أستاذك… في مكان واحد

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Dr.Huda Mohammed Fahad Aldosari

, Currently an Assistant Professor in computer Science Department . Hold a Ph.D in Machine Learning, with strong research focus in the areas of AI, ML, IoT, cybersecurity and data science Assistant Professor College of Engineering in Wadi Addawasir
  • Wadi Aldawasir
  • 011-588-8860
  • hu.aldosari@psau.edu.sa
  • Curriculum Vitae
  • Publications

Publications

  • Vaiyapuri T, Aldosari H. SUQ-3: A Three Stage Coarse-to-Fine Compression Framework for Sustainable Edge AI in Smart Farming. Sustainability. 2025; 17(12):5230. https://doi.org/10.3390/su17125230
  • Aldosari, H. M. (2024). An Expert Model Using Deep Learning for Image-based Pest Identification with the TSLM Approach for Enhancing Precision Farming. Journal of Wireless Mobile Networks Ubiquitous Computing and Dependable Applications, 15(3), 160–183. https://doi.org/10.58346/jowua.2024.i3.012
  • Vaiyapuri, T., Aldosari, H., Alharbi, G. et al. (2024). Metaheuristics based dimensionality reduction with deep learning driven false data injection attack detection for enhanced network security. Scientific Reports, 14, 18967. doi: https://doi.org/10.1038/s41598-024-69806-5
  • H. Aldosari. (2024). Garra Rufa Fish Optimization-based K-Nearest Neighbor for Credit Card Fraud Detection. 2024 International Conference on Distributed Computing and Optimization Techniques (ICDCOT), Bengaluru, India. doi: 10.1109/ICDCOT61034.2024.10516188.
  • H. Aldosari. (2024). A Hybrid Support Vector Machine with Grasshopper Optimization Algorithm based Feature Selection for Load Forecasting. 2024 International
  • Conference on Distributed Computing and Optimization Techniques (ICDCOT), Bengaluru, India. doi: 10.1109/ICDCOT61034.2024.10515470.
  • Jaganathan Y, Sanober S, Aldossary SMA, Aldosari H. (2023). Validating Wound Severity Assessment via Region-Anchored Convolutional Neural Network Model for Mobile
  • Image-Based Size and Tissue Classification. Diagnostics (Basel), 13(18):2866. doi: 10.3390/diagnostics13182866. PMID: 37761233; PMCID: PMC10529166.
  • Aldosari, H., Rsanguthevar Rajasekaran., and Ammar, R., “Generative Adversarial Neural Network and Genetic Algorithm to predict Oil & Gas Pipeline Defect Length”, ISCA, the 34th International Conference on Computer Applications in Industry & Engineering, 2021 November 2nd
  • Aldosari, H., Elfouly, R.S., and Ammar, R., “Optimal Gaussian Process Regression Model for Prediction of Oil and Gas Pipelines Defect Length”, ISCA, the 34 th International Conference on Computer Applications in Industry & Engineering, 2021 November 2nd
  • M. Alsulami, R. Elfouly, R. Ammar, H. Aldosari and A. Alenizi, "Deployment of Multiple Computing Systems in Underwater Wireless Sensor Networks", 2020 IEEE International Symposium on Signal Processing & Information Technology (ISSPIT), Kentuky, United State of America, 2020.
  • Aldosari, H., Elfouly, R.S., Ammar, R. and Alsulami, M., “Performance of New Monitoring Architectures for Underwater Oil/Gas Pipeline using Hyper-Sensors”, 2016 IEEE International Conference on Cloud Computing Technology & Science (CloudCom) (pp. 590-595). IEEE, 2020, July.
  • Aldosari, H., Elfouly, R.S., Ammar, R. and Alsulami, M., “Optimal Artificial Neural Network Model for Prediction of Oil & Gas Pipelines Defect Length”, CSCI (pp. 307-316), 2020, December.
  • Aldosari, H., Elfouly, R.S., and Ammar, “Evaluation of Machine Learning Based Regression Techniques for Prediction of Oil & Gas Pipelines Defect Length”, CSCI (pp. 317-325), 2020, December.
  • Aldosari, H., Elfouly, R.S., Ammar, R. and Alsulami, M., “New Monitoring Architectures for Underwater Oil/Gas Pipeline using Hyper sensors”, CATA (pp. 307-316), 2020, March.
  • M. Alsulami, R. Elfouly, R. Ammar, H. Aldosari and A. Alenizi, "Ideal Number of Computers for Real-Time Underwater Computing Systems", 2019 IEEE International Symposium on Signal Processing & Information Technology (ISSPIT), Ajman, United Arab Emirates, 2019, pp.

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