Comparative Study on Arabic Text Classification: Challenges and Opportunities by Abualigah, Laith

“…Based on the reviewed researches, SVM and Naive Bayes were the most widely used classifiers for Arabic text classification, while more effort is needed to develop and to implement flexible Arabic text classification methods and classifiers.…”
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A Bayesian Approach to Feature Selection in Classification Problems by Emarly, Maher

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Hybrid model for precise hepatitis-C classification using improved random forest and SVM method by Umesh Kumar Lilhore (17727684)

Salak Image Classification Method Based Deep Learning Technique Using Two Transfer Learning Models by Theng, Lau Wei

“…There are many techniques that can be used for fruit classification using computer vision technology. Deep learning is the most promising algorithm compared to another Machine Learning (ML) algorithm. …”
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A Comparative Study between Modals in ESL/EFL Tertiary Textbooks and Actual Use by EFL Teachers by Al-Jaboori, Ali

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Target Detection Using Learning Methods by Sahnoon, Mohammad Moufeed

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Enhancing Bearing Fault Diagnosis Using Transfer Learning and Random Forest Classification: A Comparative Study on Variable Working Conditions by Durjay Saha (21633095)

“…In this study, raw vibrational accelerometer data of variable working conditions is preprocessed using the window length and stride method to generate a data format suitable for evaluating the proposed model. …”

Efficient Detection of Hepatic Steatosis in Ultrasound Images Using Convolutional Neural Networks: A Comparative Study by Fahad M. Alshagathrh (19365478)

Intelligent Fusion of Deep Features for Improved Waste Classification by Kashif Ahmad (12592762)

“…To achieve reliable waste classification capability, we propose a novel approach, that we name double fusion, which optimally combines multiple deep learning models using feature and score-level fusion methods. …”

LDSVM: Leukemia Cancer Classification Using Machine Learning by Abdul Karim (417009)

Improved Machine Learning for Multiclass Fault Classification in Industrial Processes by Khaled Dhibi (16891524)

“…Experimental results on a large-scale dataset demonstrate improved performance compared to existing methods, achieving a high accuracy rate. …”

FPGA-Based Network Traffic Classification Using Machine Learning by Elnawawy, Mohammed

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Classification of Cognitive Workload Levels under Vague Visual Stimulation by Mahmoud, Rwan Adil Osman

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Supervised term-category feature weighting for improved text classification by Attieh, Joseph

“…Hence, choosing a suitable method for term weighting is of major importance and can help increase the effectiveness of the classification task. …”
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Feature fusion based on joint sparse representations and wavelets for multiview classification by Younes Akbari (14150781)

“…Generally, a dataset can be created in different views, features, or modalities. To improve the classification rate, local information is shared among different views by various fusion methods. …”

Cancerous and Non-Cancerous MRI Classification Using Dual DCNN Approach by Zubair Saeed (19325647)

“…Unlike traditional machine learning methods requiring manual feature extraction, DL models are adept at handling complex data like MRIs and excel in classification tasks, making them well-suited for medical image analysis applications. …”

Lung cancer medical images classification using hybrid CNN-SVM by Abdulrazak Yahya Saleh (18520026)

“…This paper presents an image classification method based on the hybrid Convolutional Neural Network (CNN) algorithm and Support Vector Machine (SVM). …”

Benchmark on a large cohort for sleep-wake classification with machine learning techniques by Joao Palotti (8479842)

Active Learning Based Federated Learning for Waste and Natural Disaster Image Classification by Lulwa Ahmed (16869936)

“…Promising results are obtained on both applications resulting in comparable results against the best-case scenario where each sample is manually analyzed and annotated (Baseline 1), and improvement of 3.1% and 4% with best methods respectively over the training sets with irrelevant images on natural disaster and waste classification datasets (Baseline 2).…”

Suspicious Behavior Detection with Temporal Feature Extraction and Time-Series Classification for Shoplifting Crime Prevention by Nazir, Amril

“…The extracted temporal features are then modeled as a time-series classification problem. The proposed method was tested on the popular UCF Crime dataset, and benchmarked against the current state-of-the-art robust temporal feature magnitude (RTFM) method, which relies on the Inflated 3D ConvNet (I3D) preprocessing method. …”
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