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  1. 1
    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach

    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

    Published 2009
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  2. 2
    Application of Decision Trees in Athlete Selection: A Cart Algorithm Approach

    Application of Decision Trees in Athlete Selection: A Cart Algorithm Approach by Riska Wahyu, Romadhonia, A'yunin, Sofro, Danang, Ariyanto, Dimas Avian, Maulana, Junaidi Budi, Prihanto

    Published 2023
    “…This study investigates the application of Decision Trees (DTs), a non-parametric supervised learning method, renowned for its simplicity, interpretability, and wide applicability in various domains, including machine learning for classification and regression tasks. …”
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  3. 3
    An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)

    An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

    Published 2024
    “…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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  4. 4
    Data Analysis and Rating Prediction on Google Play Store Using Data-Mining Techniques

    Data Analysis and Rating Prediction on Google Play Store Using Data-Mining Techniques by Kayalvily, Tabianan, Denis, Arputharaj, Mohd Norshahriel, Abd Rani, Sarasvathi, Nahalingham

    Published 2022
    “…This study aims to predict the ratings of Google Play Store apps using decision trees for classification in machine learning algorithms. The goal of using a Decision Tree is to create a training model that can use to predict the class or value of the target variable by learning simple decision rules inferred from prior data. …”
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  5. 5
    Development Of Semi-Automatic Liver Segmentation Method For Three-Dimensional Computed Tomography Dataset

    Development Of Semi-Automatic Liver Segmentation Method For Three-Dimensional Computed Tomography Dataset by Chiang, Yi Fan

    Published 2017
    “…In post-processing, the contour of liver is smooth by binary Gaussian filter. The liver segmentation program with proposed algorithm is evaluated with CT datasets obtained from SLIVER07 to prove its effectiveness in liver segmentation. …”
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  6. 6
    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
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  7. 7
    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms

    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

    Published 2018
    “…The experimental results are also thoroughly evaluated and verified via non-parametric statistical analysis. Based on the obtained experimental results, the OGC, DPSO, and VDEO frameworks achieved an average enhancement up to 24.36%, 9.38%, and 11.98% of classification accuracy, respectively. …”
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  8. 8
    Image Splicing Detection With Constrained Convolutional Neural Network

    Image Splicing Detection With Constrained Convolutional Neural Network by Lee, Yang Yang

    Published 2019
    “…The constrained layer enables the CNN model to learn the required features directly from ubiquitous image input and then performs classification. …”
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  9. 9
    Oil palm mapping over Peninsular Malaysia using Google Earth Engine and machine learning algorithms

    Oil palm mapping over Peninsular Malaysia using Google Earth Engine and machine learning algorithms by Shaharum, Nur Shafira Nisa, Mohd Shafri, Helmi Zulhaidi, Wan Ab. Karim Ghani, Wan Azlina, Samsatli, Sheila, Al-Habshi, Mohammed Mustafa, Yusuf, Badronnisa

    Published 2020
    “…In this study, 30 m Landsat 8 data were processed using a cloud computing platform of Google Earth Engine (GEE) in order to classify oil palm land cover using non-parametric machine learning algorithms such as Support Vector Machine (SVM), Classification and Regression Tree (CART) and Random Forest (RF) for the first time over Peninsular Malaysia. …”
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  10. 10
    Framework for stream clustering of trajectories based on temporal micro clustering technique

    Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

    Published 2018
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  11. 11
    Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu

    Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu by Sabtu, Melati

    Published 2005
    “…The project used Back-propagation Neural Network for the algorithm to classified images. …”
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  12. 12
    Word segmentation of output response for sign language devices

    Word segmentation of output response for sign language devices by Za'bah, Nor Farahidah, Muhammad Nazmi, Ahmad Amierul Asyraf, Azman, Amelia Wong

    Published 2020
    “…The proposed text segmentation method in this work is by using the dynamic programming and back-off algorithm, together with the probability score using word matching with an English language text corpus. …”
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  13. 13
    Supervised retinal vessel segmentation based on neural network using broader aging dataset

    Supervised retinal vessel segmentation based on neural network using broader aging dataset by Che Azemin, Mohd Zulfaezal, Abd Hamid, Fadilah, Mohd Tamrin, Mohd Izzuddin, Muhamad Amin, Anang Hudaya

    Published 2014
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  14. 14
    Interactive blood vessel segmentation from retinal fundus image based on canny edge detector

    Interactive blood vessel segmentation from retinal fundus image based on canny edge detector by Ibrahim, Haidi, Ooi, Alexander Ze Hwan, Soo, Siang Teoh, Embong, Zunaina, Abd Hamid, Aini Ismafairus, Zainon, Rafidah, Shir, Li Wang, Theam, Foo Ng, Hamzah, Rostam Affendi

    Published 2021
    “…The program will draw out the vessel edges. After that, those vessel edges will be segmented to bring focus on its details or detect the abnormal vessel. …”
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  15. 15
    Accuracy of advanced deep learning with tensorflow and keras for classifying teeth developmental stages in digital panoramic imaging

    Accuracy of advanced deep learning with tensorflow and keras for classifying teeth developmental stages in digital panoramic imaging by Norhasmira, Mohammad, Anuar Mikdad, Muad, Rohana, Ahmad, Mohd Yusmiaidil, Putera Mohd Yusof

    Published 2022
    “…Results: Image segmentation using the DP-AC algorithm enhanced the visibility of the image features in the region of interest while suppressing the image’s background noise. …”
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  16. 16
    Fast recovery of unknown coefficients in DCT-transformed images

    Fast recovery of unknown coefficients in DCT-transformed images by Ong, Sim Ying, Li, Shujun, Wong, Kok Sheik, Tan, Kuan Yew

    Published 2017
    “…In this paper, we propose a fast hierarchical DCT coefficients recovery method by combining image segmentation and linear programming. In theory the proposed method can reduce the overall time complexity by a linear factor which is the number of image segments used. …”
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  17. 17
    STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION

    STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION by Adil H., Khan, Dayang Nurfatimah, Awang Iskandar, Jawad F., Al-Asad, SAMIR, EL-NAKLA, SADIQ A., ALHUWAIDI

    Published 2021
    “…A boost ensemble learning algorithm using Support Vector Machines (SVM) as initial classifiers and Artificial Neural Networks (ANN) as a final classifier is employed to learn the patterns of different skin lesion class features. …”
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  18. 18
    Development of compound clustering techniques using hybrid soft-computing algorithms

    Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

    Published 2006
    “…The feed forward and radial basis functions networks show higher learning capabilities than support vector machines and rough set classifier in the classification of datasets comprising more than two classes. …”
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    Monograph
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  19. 19
    Optimal step-function approximation of load duration curve using evolutionary programming (EP) / Eda Azuin Othman

    Optimal step-function approximation of load duration curve using evolutionary programming (EP) / Eda Azuin Othman by Othman, Eda Azuin

    Published 2014
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  20. 20
    Moving detection using cellular neural network (CNN)

    Moving detection using cellular neural network (CNN) by Prema Latha, Subramaniam

    Published 2008
    “…The algorithm created is used to detect the ball in the images. …”
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    Undergraduates Project Papers
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