Various Faults Classification of Industrial Application of Induction Motors Using Supervised Machine Learning: A Comprehensive Review by Rehaan Hussain (22302742)

Exploring Semi-Supervised Learning Algorithms for Camera Trap Images by Sajun, Ali Reza

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Addressing Binary Classification over Class Imbalanced Clinical Datasets Using Computationally Intelligent Techniques by Vinod Kumar (48743)

Scalable Nonparametric Supervised Learning for Streaming and Massive Data: Applications in Healthcare Monitoring and Credit Risk by Mohamed Chaouch (17983846)

“…<p dir="ltr">This paper introduces novel nonparametric supervised learning techniques for classifying massive datasets, addressing key limitations of existing methods in Big and Streaming Data framework. …”

A Machine Learning Approach to Predicting Diabetes Complications by Jian, Yazan Khaled

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Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images by Ahila A (18394806)

On the protection of power system: Transmission line fault analysis based on an optimal machine learning approach by Md. Sihab Uddin (17542488)

Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges by Muhammad Usama (3629090)

“…<p dir="ltr">While machine learning and artificial intelligence have long been applied in networking research, the bulk of such works has focused on supervised learning. Recently, there has been a rising trend of employing unsupervised machine learning using unstructured raw network data to improve network performance and provide services, such as traffic engineering, anomaly detection, Internet traffic classification, and quality of service optimization. …”

Application of Data Mining to Predict and Diagnose Diabetic Retinopathy by Haniyeh, Maryam

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A Study of the Impact of the Climate and Land-use/Land-cover (LULC) Changes on the UAE Mangrove Forests over the Period 1990-2020 by Raihan, Asif

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Heuristic approaches for optimizing the performance of rule-based classifiers by Harmanani, Haidar

“…Rule-based classifiers are supervised learning techniques that are extensively used in various domains. …”
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Metaheuristic Optimization Algorithms for Training Artificial Neural Networks by Mansour, Nashat

“…Training neural networks is a complex task that is important for supervised learning. A few metaheuristic optimization techniques have been applied to increase the effectiveness of the training process. …”
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Hyperspectral mapping of crust and mantle rocks in the UAE Al-Hajar mountains: Locating raw materials for Martian regolith simulants by Pavlopoulos, Kosmas

“…Feature extraction and hyperspectral classification such as the supervised Spectral Angle Mapper (SAM) and Spectral Feature Fitting (SFF) methods are carried out to map the different lithologies in the extended regions of interest. …”
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Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis by Hassan Ali (3348749)

“…However, research has shown that the adversarial vulnerabilities of deep learning networks manifest themselves when DL is used for NLP tasks. Most mitigation techniques proposed to date are supervised—relying on adversarial retraining to improve the robustness—which is impractical. …”

Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis by Hassan, Ali

“…However, research has shown that the adversarial vulnerabilities of deep learning networks manifest themselves when DL is used for NLP tasks. Most mitigation techniques proposed to date are supervised—relying on adversarial retraining to improve the robustness—which is impractical. …”
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The Use of Supply Chain Metrics in Lebanon by Huballah, Zeina

“…The results of the survey are analyzed via two machine learning techniques – an unsupervised clustering technique (kMeans) to identify companies with similar behavior relative to the SCOR metrics and a supervised learning technique (Classification Trees) to ascertain which company demographics (ie industry, age, size, age of employees, and SCOR familiarity) dictate cluster membership.…”
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Precision nutrition: A systematic literature review by Daniel Kirk (17302798)

“…Four machine learning tasks are seen in the form of regression, classification, recommendation and clustering, with most of these utilizing a supervised approach. …”