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Support Vector Machines (SVM) in Test Extraction
Published 2006“…In this project, Support Vector Machines (SVM) is studied and experimented by the implementation ofa textual extractor. …”
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Final Year Project -
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Support Vector Machines (SVM) in Test Extraction
Published 2006“…In this project, Support Vector Machines (SVM) is studied and experimented by the implementation ofa textual extractor. …”
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Prediction of COVID-19 outbbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman
Published 2024“…In response to the unprecedented challenges posed by the COVID-19 pandemic, this research project presents a systematic approach to outbreak prediction, specifically advocating for the implementation of Support Vector Machine (SVM) algorithms. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…Thus, TC suggested being the main step in data pre-processing for mountainous terrain before the RBF-based SVM classification process. …”
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Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…The image data is pre-processed; the CNN algorithm is then applied to classify the ASD and non-ASD, and the steps of implementing the CNN algorithm are clearly stated. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The support vector machines (SVM) algorithm obtained the overall best results of 94.5% accuracy, 91.8% precision, 91.7% recall, and 91.1% f-Measure while the naïve bayes (NB) algorithm obtained the best AUC score of 0.944 with the tweet data of Dato Seri Anwar. …”
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Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif
Published 2014“…Support Vector Machine (SVM) is among the popular learning algorithm for classification in soft computing techniques. …”
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Research Reports -
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Oil palm mapping over Peninsular Malaysia using Google Earth Engine and machine learning algorithms
Published 2020“…However, RF extracted oil palm information better than the SVM. The algorithms were compared and the McNemar's test showed significant values for comparisons between SVM and CART and RF and CART. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Financial time series predicting using machine learning algorithms
Published 2013“…Thereafter, Artificial Neural Network (ANN) and Support Vector Machine (SVM) algorithms are implemented separately to train with the trend patterns for predicting the movement direction of financial trends. …”
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SVM driven approach for detecting DoS attacks in SDN environment
Published 2025“…To address this challenge, we propose a novel approach that efficiently detects DoS attacks by implementing a packet inspection process using a queuing mechanism, followed by machine learning classification using SVM and KNN algorithms. …”
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Development of colorization of grayscale images using CNN-SVM
Published 2021“…Support Vector Machine (SVM) regression was used at the final stage. The proposed algorithm was implemented using Python with Keras and Tensorflow libraries in Google Colab. …”
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Book Chapter -
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The formulation of a transfer learning pipeline for the classification of the wafer defects
Published 2023“…This often causes misjudgment and inconsistency result between different personnel. Automated processes have been used commonly in recent years, with the judgement done by using conventional image processing algorithm. …”
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Classification Of Cervical Cancer Stage From Pap Smear Tests
Published 2019“…The proposed approach will implement stages of image pre-processing, feature selection and extraction as well as classification of classes. …”
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Final Year Project -
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…Statistical techniques such as Anisotropic Diffusion Filter (ADF), local contrast enhancement, and haze reduction in the CIELAB colour space, are incorporated in the proposed algorithms for the pre-processing step. Hair removal is implemented through black-hat morphological processing and total variation based inpainting. …”
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Mixed waste classification based on vision inspection / Hassan Mehmood Khan
Published 2022“…The best 17 resulting features were used for the next process. Four classification algorithms specifically the Cubic SVM (C.SVM), Quadratic SVM (Q.SVM), Ensemble Bagged Trees (EBT) and k-Nearest Neighbor (kNN) are employed to test the classification accuracy. …”
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