Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn... by Mohamed, AlShuweihi

“…The second major contribution is the design and construction of a Logistic Regression (LR) ML binary classification model with an accuracy of 87% and F1-score of 89%. …”
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A Bayesian Deep Learning Approach With Convolutional Feature Engineering to Discriminate Cyber-Physical Intrusions in Smart Grid Systems by Devinder Kaur (264278)

A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata by Siddiqui, Ansah Juned

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Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine by Debendra Muduli (20748758)

“…For mass fundus image-based glaucoma classification, an improved automated computer-aided diagnosis (CAD) model performing binary classification (glaucoma or healthy), allowing ophthalmologists to detect glaucoma disease correctly in less computational time. …”

VHDRA: A Vertical and Horizontal Intelligent Dataset Reduction Approach for Cyber-Physical Power Aware Intrusion Detection Systems by Hisham A. Kholidy (18891802)

“…This poses some problems for the large volume data and hinders the scalability of any detection system. In this paper, we introduce VHDRA, a Vertical and Horizontal Data Reduction Approach, to improve the classification accuracy and speed of the NNGE algorithm and reduce the computational resource consumption. …”

Analysis of Using Machine Learning to Enhance the Efficiency of Facilities Management in the UAE by ULLAH, SAAD

“…Seasonal thresholds are set for sensor values, and the algorithm detects hazardous trends when values exceed safe limits, correlating them with related sensors to generate combined variables and error codes. …”
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Developing a framework for using face recognition in transit payment transactions by HABEH, ORABI MOHAMMAD ABDULLAH

“…A number of combined algorithms and classifiers are proposed to use in this solution based on the encouraging outcomes observed from the systematic literature review and experts’ survey, including Local Binary Pattern descriptor, Haar-Like Descriptor, Ada Boost, Cascade classifiers, Affine Transformation, Histogram Equalization, Gaussian Filter, Principal Component Analysis which are embedded in OpenCV or MATLAB application. …”
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