Search Results - (( learning segmentation mining algorithm ) OR ( java application optimisation algorithm ))

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  1. 1
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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  2. 2
    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
    “…On the other hand, trajectories preprocessing such as segmentation and noise points filtering is a vital step which precedes the mining task. …”
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  3. 3
    A detailed description on unsupervised heterogeneous anomaly based intrusion detection framework

    A detailed description on unsupervised heterogeneous anomaly based intrusion detection framework by Udzir, Nur Izura, Hajamydeen, Asif Iqbal

    Published 2019
    “…More effort has been taken in utilizing the data mining and machine learning algorithms to construct anomaly based intrusion detection systems, but the dependency on the learned models that were built based on earlier network behaviour still exists, which restricts those methods in detecting new or unknown intrusions. …”
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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
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  5. 5
    Review of Wheat Disease Classification and Severity Detection Models

    Review of Wheat Disease Classification and Severity Detection Models by Hongyan, Zang, Annie, Joseph, Shourong, Zhang, Rong, Liu, Wanzhen, Wang

    Published 2023
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  6. 6
    Automated feature extraction on brain MRI images for predicting multiple sclerosis patient disability

    Automated feature extraction on brain MRI images for predicting multiple sclerosis patient disability by M. Muslim, Ali

    Published 2022
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  7. 7
    Web-based expert system for material selection of natural fiber- reinforced polymer composites

    Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

    Published 2015
    “…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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  8. 8
    Prediction of ADHD from a small dataset using an adaptive EEG theta/beta ratio and PCA feature extraction

    Prediction of ADHD from a small dataset using an adaptive EEG theta/beta ratio and PCA feature extraction by Sase, Takumi, Othman, Marini

    Published 2022
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  9. 9
    Prediction of ADHD from a small dataset using an adaptive EEG Theta/Beta Ratio and PCA feature extraction

    Prediction of ADHD from a small dataset using an adaptive EEG Theta/Beta Ratio and PCA feature extraction by Sase, Takumi, Othman, Marini

    Published 2022
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  10. 10
    Validation of deep convolutional neural network for age estimation in children using mandibular premolars on digital panoramic dental imaging / Norhasmira Mohammad

    Validation of deep convolutional neural network for age estimation in children using mandibular premolars on digital panoramic dental imaging / Norhasmira Mohammad by Mohammad, Norhasmira

    Published 2022
    “…The semi-automated dental staging system developed in this study is based on the Malay children’s population and uses a brain-inspired learning algorithm termed "deep learning". The methodology is comprised of four major steps: image preprocessing, which adheres to the inclusion criteria for panoramic dental radiographs, segmentation, and classification of mandibular premolars according to Demirjian's staging system using the Dynamic Programming-Active Contour (DP-AC) method and Deep Convolutional Neural Network (DCNN), respectively, and statistical analysis. …”
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