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An Automated System For Classifying Conference Papers
Published 2021“…A randomised stratified 5- fold cross validation was then applied on several data mining algorithms and evaluated using the F-measure as a metric. …”
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Final Year Project / Dissertation / Thesis -
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Email spam classification based on deep learning methods: A review
Published 2025“…Deep learning has become a potent collection of techniques for addressing intricate issues such as spam classification in recent times. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This reserarch adapted a methodology of computer vision and algorithms that exploit image segmentation, feature extraction and fuzzy classification to guide the research activities. …”
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Thesis -
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Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection
Published 2019“…However, the training datasets usually compose feature sets of irrelevant or redundant information, which impacts the performance of classification, and traditional learning algorithms such as backpropagation suffer from known issues, including slow convergence and the trap of local minimum. …”
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5
BONE AGE ANALYSIS FROM BONE X-RAY
Published 2018“…Manual bone age assessment basically take time f task in for radiologist and there are always issue related to intra observer and inter observer differences. …”
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Final Year Project -
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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Thesis -
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The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer
Published 2023“…Moreover, this paper also defined the basic requirements for creating a skin cancer detection application, which revolves around two main issues: the full segmentation image and the tracking of the lesion on the skin using deep learning. …”
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Article -
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Satellite Image Segmentation Using Thresholding Technique
Published 2017“…Image segmentation is one of the basic techniques of image processing and computer vision. …”
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Thesis -
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An ensemble feature selection method to detect web spam
Published 2018“…In addition, it improves classification metrics in comparison to basic feature selection methods.…”
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A Machine Learning Classification Approach to Detect TLS-based Malware using Entropy-based Flow Set Features
Published 2022“…Furthermore, using the basic features, TLSMalDetect achieved the highest accuracy of 93.69% by Naïve Bayes (NB) among the ML algorithms applied. …”
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Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome
Published 2014“…In the development of the “hybrid AI-based” classification models, the proposed model (K1-K2- NN), was basically introduced through combining AI approaches of modified K-NN, genetic algorithm (GA), Fisher’s discriminant ratio (FDR) and class separability criteria (CSC). …”
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Early detection of spots high water saturation for landslide prediction using thermal imaging analysis
“…The performance of these segmentation algorithms are measured using misclassification error. …”
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Research Report -
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A review of Convolutional Neural Networks in Remote Sensing Image
Published 2019“…Recently, convolutional neural network based deep learning algorithm has achieved a series of breakthrough research results in the fields of objective detection, image semantic segmentation and image classification, etc. …”
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Conference or Workshop Item -
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Early detection of high water saturation spots for landslide prediction using thermal image analysis
Published 2018“…There are three segmentation algorithm used in this study which are HSV, K-Means and Feature Matching. …”
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Hybrid Neural Network With K-Means For Forecasting Response Candidate In Direct Marketing
Published 2014“…This research concerns on binary classification which is classified into two classes. Those classes are yes and no. …”
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Machine Learning Based Two Phase Detection and Mitigation Authentication Scheme for Denial-of-Service Attacks in Software Defined Networks
Published 2024“…In this research, Two-Phase Authentication of Attack Detection (TPAAD) scheme is proposed and investigated for detection and mitigation of DoS attacks in SDN to increase the performance of the above-mentioned issues. This scheme incorporates machine learning techniques by utilizing Support Vector Machine (SVM) and K-Nearest Neighbors (KNN) classification algorithms to accurately identify and handle malicious network traffic following the initial packet filtration process that identifies abnormal traffic. …”
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Text-based emotion prediction system using machine learning approach
Published 2020“…Several market challenges facing in the advancement of emotion analysis with accuracy being the main issue. Therefore, four supervised machine learning classification algorithms such as Multinomial Naïve Bayes, Support Vector Machine, Decision Trees, and kNearest Neighbors were investigated. …”
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