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  1. 1

    Classification of Immunosignature Using Random Forests for Cancer Diagnosis by Zarzar, Mouayad, Razak, Eliza, Htike@Muhammad Yusof, Zaw Zaw, Yusof, Faridah

    Published 2015
    “…In this work, we will develop a robust classification model that can be utilized in cancer diagnosis using immunofingerprint data. …”
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    Proceeding Paper
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    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

    Published 2011
    “…Basically, the proposed of FUHS16, UHDS16 and UHDS8 algorithm produces the best motion vector estimation finding based on the block-based matching criteria. …”
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    Book Chapter
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    Deep learning detector for pests and plant disease recognition by Ileladewa, Oluwatimilehin Adekunle

    Published 2020
    “…Meanwhile, evolution in deep convolutional neural networks for image classification has rapidly improved the accuracy of object detection, classification and system recognition. …”
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    Final Year Project / Dissertation / Thesis
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    Y-type Random 2-satisfiability In Discrete Hopfield Neural Network by Guo, Yueling

    Published 2024
    “…Finally, a new logic mining model namely Y-Type Random 2-Satisfiability Reverse Analysis was proposed, which showed optimal performances in terms of several metrics as compared to the existing classification models. …”
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    Thesis
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    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…However, the learning complexity of classification is increased due to the expansion number of learning model. …”
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    Thesis
  9. 9

    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

    Published 2019
    “…Block Matching Algorithm (BMA) is a technique used to minimize the computational complexity of motion estimation in video coding application. …”
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    Thesis
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    Digital economy tax compliance model in Malaysia using machine learning approach by Raja Azhan Syah Raja Wahab, Azuraliza Abu Bakar

    Published 2021
    “…The experimental results show that the ensemble method can improve the single classification model’s accuracy with the highest classification accuracy of 87.94% compared to the best single classification model. …”
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    Article
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    Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

    Published 2021
    “…Feature selection was used to sort out key features for further classification. News classification into factors affecting stock market turning point was done using Naïve Bayes, Deep Learning, Generalized Linear Model (GLM) and Support Vector Machine (SVM). …”
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    Book Section
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    Performance Analysis of Motion Estimation Algorithms on Digital Video Images by Ali, Nur Alisa, Ja'afar, Abd Shukur, Abd Rahim, Rosman, Mohammed Napiah, Zul Atfyi Fauzan, Md Yusop, Azdiana, Meor Said, Maizatul Alice

    Published 2011
    “…In the BMME, search patterns with different shapes or sizes and the center-biased characteristics of motion vector (MV) have large impact on the search speed (search points) and peak signal-to-noise ratio (PSNR) as the quality of video images. These basic algorithms are Full Search and other two fast search methods. …”
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    Article
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    Power System State Estimation In Large-Scale Networks by NURSYARIZAL MOHD NOR, NURSYARIZAL

    Published 2010
    “…The gain and the Jacobian matrices associated with the basic algorithm require large storage and have to be evaluated at every iteration, resulting in more computation time. …”
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    Thesis
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    Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

    Published 2004
    “…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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    Article
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