Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data حسب Arshad, Muhammad Arbab

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

"…The focus of this survey paper is to provide an overview of applications of unsupervised learning in the domain of networking. We provide a comprehensive survey highlighting recent advancements in unsupervised learning techniques, and describe their applications in various learning tasks, in the context of networking. …"

Breast Density Estimation in Mammograms Using Unsupervised Image Segmentation حسب Alhusari, Khaldoon

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Integrating binary classification and clustering for multi-class dysarthria severity level classification: a two-stage approach حسب Afnan S. Al-Ali (22224889)

"…We begin by employing binary classification to differentiate control from dysarthric cases by experiencing eight different feature extraction techniques and two classifiers in order to support the largest amount of dysarthric cases to the second stage, where k-means clustering uncovers hidden patterns and boundaries within dysarthria severity levels, enabling a more nuanced understanding of the disorder. …"

Use of Data Mining Techniques to Detect Fraud in Procurement Sector حسب AL HAMMADI, SUMAYYA ABDULLA

"…All techniques also will be studied; they include clustering, tracking patterns, classifications and outlier detection. …"
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InShaDe: Invariant Shape Descriptors for visual 2D and 3D cellular and nuclear shape analysis and classification حسب Khaled Al-Thelaya (17302711)

"…We demonstrate the capabilities of our framework in the context of visual analysis and unsupervised classification of 2D histology images and 3D nuclear envelopes extracted from serial section electron microscopy stacks.…"

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

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Multi Self-Organizing Map (SOM) Pipeline Architecture for Multi-View Clustering حسب Saadia Jamil (22045946)

"…<p dir="ltr">Clustering has proved to be a successful classification method when it comes to dealing with multiview data. …"

Target Detection Using Learning Methods حسب Sahnoon, Mohammad Moufeed

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Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis حسب Hassan Ali (3348749)

"…This work introduces a novel, unsupervised detection methodology for detecting adversarial inputs to NLP classifiers. …"

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

"…This work introduces a novel, unsupervised detection methodology for detecting adversarial inputs to NLP classifiers. …"
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The Use of Supply Chain Metrics in Lebanon حسب 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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A Machine Learning Approach to Predicting Diabetes Complications حسب Jian, Yazan Khaled

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An Efficient Brain Tumor Segmentation Method Based on Adaptive Moving Self-Organizing Map and Fuzzy K-Mean Clustering حسب Surjeet Dalal (4906894)

"…AMSOM is an artificial neural technique whose training is unsupervised. This research utilized the online Kaggle Brats-18 brain tumor dataset. …"