M
Mohib Ullah
Researcher at University of Agriculture, Peshawar
Publications - 18
Citations - 155
Mohib Ullah is an academic researcher from University of Agriculture, Peshawar. The author has contributed to research in topics: User profile & The Internet. The author has an hindex of 3, co-authored 18 publications receiving 29 citations. Previous affiliations of Mohib Ullah include Capital University.
Papers
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Journal ArticleDOI
Acute Myeloid Leukemia (AML) Detection Using AlexNet Model
Maneela Shaheen,Rafiullah Khan,R. R. Biswal,Mohib Ullah,Atif Khan,M. Irfan Uddin,Mahdi Zareei,Abdul Waheed,Abdul Waheed +8 more
TL;DR: In this article, an AlexNet-based classification model was proposed to detect Acute Myeloid Leukemia (AML) in microscopic blood images and compared its performance with LeNet-5-based model in Precision, Recall, Accuracy, and Quadratic Loss.
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Remote Diagnosis and Triaging Model for Skin Cancer Using EfficientNet and Extreme Gradient Boosting
Irfan Ullah Khan,Nida Aslam,Talha Anwar,Sumayh S. Aljameel,Mohib Ullah,Rafiullah Khan,Abdul Rehman,Nadeem Akhtar +7 more
TL;DR: In this article, the authors proposed an automated skin cancer diagnosis and triaging model and explored the impact of integrating clinical features in the diagnosis and enhance the outcomes achieved by the literature study.
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EEWMP: An IoT-Based Energy-Efficient Water Management Platform for Smart Irrigation
Rafi Ullah,Arbab Waseem Abbas,Mohib Ullah,Rafiullah Khan,Irfan Ullah Khan,Nida Aslam,Sumayh S. Aljameel +6 more
TL;DR: In this article, the authors proposed an energy-efficient water management platform (EEWMP), an improved version of SWAMP, which uses field-deployed sensors, sinks, fusion centres, and open-source clouds.
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QuPiD Attack: Machine Learning-Based Privacy Quantification Mechanism for PIR Protocols in Health-Related Web Search
Rafiullah Khan,Rafiullah Khan,Arshad Ahmad,Alhuseen Omar Alsayed,Muhammad Binsawad,Muhammad Arshad Islam,Mohib Ullah,Mohib Ullah +7 more
TL;DR: This paper presents QuPiD (query profile distance) attack: a machine learning-based attack that evaluates the effectiveness of UUP in privacy protection, and determines the distance between the user’s profile (web search history) and upcoming query using a proposed novel feature vector.
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Privacy Exposure Measure: A Privacy-Preserving Technique for Health-Related Web Search
TL;DR: PEM assesses the similarity between the user's profile and query before posting to WSE and assists the user in avoiding privacy exposure, and offers more privacy to the user even in case of machine-learning attack.