A Bayesian Deep Learning Approach With Convolutional Feature Engineering to Discriminate Cyber-Physical Intrusions in Smart Grid Systems حسب Devinder Kaur (264278)

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... حسب Mohamed, AlShuweihi

"…LR with the reduced feature set using the intersection between CS and RFE proved to be the best model among the tested algorithms. …"
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A Digital DNA Sequencing Engine for Ransomware Analysis using a Machine Learning Network حسب KHAN, FIROZ

"…The preprocessing of data includes remove missing value records and remove columns that have a negligible impact. The feature selection uses Grey Wolf Optimisation and Binary Search algorithms for choosing the best features out of the dataset. …"
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Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine حسب 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. …"

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

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

"…However, NNGE algorithm tends to produce rules that test a large number of input features. …"

Developing a framework for using face recognition in transit payment transactions حسب HABEH, ORABI MOHAMMAD ABDULLAH

"…On the other hand, a tremendous advancement has been noticed in the human face detection and recognition technology which mainly used to authenticate and identify person face from a group of people through detecting a unique feature of the face and ignore the background image then compare the outcomes with the registered faces in the database to identify the person. …"
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