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

“…A Master of Science thesis in Ccomputer Engineering by Muhammad Arbab Arshad entitled, “Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data”, submitted in August 2021. …”
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Supervised term-category feature weighting for improved text classification by Attieh, Joseph

“…It consists of a supervised weighting scheme defined based on a variant of the TF-ICF (Term Frequency-Inverse Category Frequency) model, embedded into three new lean classification approaches: (i) IterativeAdditive (flat), (ii) GradientDescentANN (1-layered), and (iii) FeedForwardANN (2-layered). …”
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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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Breast Density Estimation in Mammograms Using Unsupervised Image Segmentation by Alhusari, Khaldoon

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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. …”

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. …”

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

An IoT System Using Deep Learning to Classify Camera Trap Images on the Edge by Zaulkernan, Imran

“…This paper proposes an IoT architecture that uses deep learning on edge devices to convey animal classification results to a mobile app using the LoRaWAN low-power, wide-area network. …”
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Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images by Ahila A (18394806)

Self-Supervised Learning Powered by Synthetic Data From Diffusion Models: Application to X-Ray Images by Abdullah Hosseini (22466602)

“…This study explores the efficacy of synthetic data generated using diffusion models for training deep learning models within a self-supervised learning framework. …”

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

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Fast Text Classification using Lean Gradient Descent Feed Forward Neural Network for Category Feature Augmentation by Attieh, Joseph

“…The model produces category-based feature vector representations that are used to augment the document representations and perform the classification task. …”
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The effects of data balancing approaches: A case study by Paul Mooijman (4453189)

Global smart cities classification using a machine learning approach to evaluating livability, technology, and sustainability performance across key urban indices by Aya Hasan Alkhereibi (17151070)

Target Detection Using Learning Methods by Sahnoon, Mohammad Moufeed

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

Integration of nonparametric fuzzy classification with an evolutionary-developmental framework to perform music sentiment-based analysis and composition by Abboud, Ralph

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Achieving Domestic Energy Efficiency Using Micro-Moments and Intelligent Recommendations by Abdullah Alsalemi (6951986)

InShaDe: Invariant Shape Descriptors for visual 2D and 3D cellular and nuclear shape analysis and classification by 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.…”