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

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

“…A Master of Science thesis in Computer Engineering by Mohammed Elnawawy entitled, “FPGA-Based Network Traffic Classification Using Machine Learning”, submitted in November 2019. …”
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FPGA-Based Network Traffic Classification Using Machine Learning by Elnawawy, Mohammed

“…Classification approaches based on machine learning techniques have shown promising results with high levels of accuracy. …”
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Machine learning approach for the classification of corn seed using hybrid features by Aqib Ali (19680145)

“…The nine optimized features have been acquired by employing the correlation-based feature selection (CFS) technique with the Best First search algorithm. To build the classification models, Random forest (RF), BayesNet (BN), LogitBoost (LB), and Multilayer Perceptron (MLP) were employed using optimized multi-feature using (10-fold) cross-validation approach. …”

Using machine learning for disease detection. (c2013) by Jreij, Georges Antoun

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Predictive Model of Psychoactive Drugs Consumption using Classification Machine Learning Algorithms by Almahmood, Mothanna

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COVID-19 Tweets Classification during Lockdown Period Using Machine Learning Classifiers by Syed Ali Jafar Zaidi (19505617)

“…Support vector machine (SVM), random forest (RF), decision tree (DT), and k-nearest neighbor (KNN) were used for classification, while AdaBoost and convolutional neural network (CNN) were utilized for future effects. …”

An efficient approach for textual data classification using deep learning by Abdullah Alqahtani (7128143)

“…<p dir="ltr">Text categorization is an effective activity that can be accomplished using a variety of classification algorithms. In machine learning, the classifier is built by learning the features of categories from a set of preset training data. …”

On the Use of Deep Learning for Video Classification by Atiq ur Rehman (14153391)

Colon cancer classification using microarray data by Tariq Khan, Saima

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Thermal Change Index-Based Diabetic Foot Thermogram Image Classification Using Machine Learning Techniques by Amith Khandakar (14151981)

“…Machine learning approaches applied to such infrared images may have utility in the early diagnosis of diabetic foot complications. …”

The automation of the development of classification models and improvement of model quality using feature engineering techniques by Sjoerd Boeschoten (17347045)

“…<p>Recently pipelines of machine learning-based classification models have become important to codify, orchestrate, and automate the workflow to produce an effective machine learning model. …”

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

“…Traditional machine learning models often struggle in such settings. …”

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

Hybrid Neural Networks for Precise Hydronephrosis Classification Using Deep Learning by Abdus Salam (1918387)

Waste Classification for Sustainable Development Using Image Recognition with Deep Learning Neural Network Models by Meena Malik (17542089)

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

Exploring Effects of Mental Stress with Data Augmentation and Classification Using fNIRS by Khan, Malik Nasir Afzal

“…For a comprehensive evaluation, the acquired fNIRS data are classified using a variety of machine-learning approaches. Linear discriminant analysis (LDA) showed a maximum accuracy of 60%, whereas non-augmented data classified by a convolutional neural network (CNN) provided the highest classification accuracy of 73%. …”
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A Novel Big Data Classification Technique for Healthcare Application Using Support Vector Machine, Random Forest and J48 by Al-Manaseer, Hitham

“…In this study, the possibility of using and applying the capabilities of artificial intelligence (AI) and machine learning (ML) to increase the effectiveness of Internet of Things (IoT) and big data in developing a system that supports decision makers in the medical fields was studied. …”
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Cancerous and Non-Cancerous MRI Classification Using Dual DCNN Approach by Zubair Saeed (19325647)

“…DL techniques have become more and more popular in current research on brain tumor detection. 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. …”