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  1. 1
    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices

    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

    Published 2013
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  2. 2
    Performance evaluation of real-time multiprocessor scheduling algorithms

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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  3. 3
    Route Optimization System

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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  4. 4
    Development of a syncope classification algorithm from physiological signals acquired in tilt-table test

    Development of a syncope classification algorithm from physiological signals acquired in tilt-table test by Gan, Ming Hong

    Published 2023
    “…Features that selected for the classification is mean of systolic and diastolic blood pressure, standard deviation of real variability of diastolic blood pressure, and the mean of systolic blood pressure in low and high frequency ratio. …”
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  5. 5
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
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  6. 6
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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  7. 7
    Use of hybrid classification algorithm for land use and land cover analysis in data scarce environment

    Use of hybrid classification algorithm for land use and land cover analysis in data scarce environment by Al-Doski, Jwan M. Mohammed

    Published 2013
    “…In conclusion, hybrid classification as a combination of k-means and support vector machine algorithms and post-classification comparison change detection technique can be used to monitor land cover changes in Halabja city, Iraq. …”
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  8. 8
    Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System

    Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System by Al-Hameli, Bassam Abdo, Alsewari, Abdulrahman A., Alraddadi, Abdulaziz Saleh, Aldhaqm, Arafat

    Published 2021
    “…The proposed method has three steps: preprocessing, feature selection and classification. Several combinations of Harmony search algorithm, genetic algorithm, and particle swarm optimization algorithm are examined with K-means for feature selection. …”
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  9. 9
    Application of Fuzzy C-Means with YCbCr and DenseNet-201 for Automated Corn Leaf Disease Detection

    Application of Fuzzy C-Means with YCbCr and DenseNet-201 for Automated Corn Leaf Disease Detection by Chyntia Jaby, Entuni

    Published 2021
    “…This is due to instability and complexity of the network. Hence, algorithm that performed better is required. Thus, in this study, image segmentation method of Fuzzy C-Means with YCbCr and image classification method of DenseNet-201 to detect plant leaf diseases is proposed. …”
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  10. 10
    An efficient likelihood-based modulation classification algorithm for multiple-input multiple-output systems

    An efficient likelihood-based modulation classification algorithm for multiple-input multiple-output systems by Bahloul, M.R., Yusoff, M.Z., Abdel-Aty, A.-H., Saad, M.N.M.

    Published 2016
    “…This can be performed by employing a Modulation Classification (MC) algorithm, which can be feature-based or likelihood-based. …”
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  11. 11
    Classification Of Hand Movements Based On Discrete Wavelet Transform And Enhanced Feature Extraction

    Classification Of Hand Movements Based On Discrete Wavelet Transform And Enhanced Feature Extraction by Too, Jing Wei, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

    Published 2019
    “…The extracted features are then fed into the machine learning algorithm for classification process. Four popular machine learning algorithms include k-nearest neighbor (KNN), linear discriminate analysis (LDA), Naïve Bayes (NB) and support vector machine (SVM) are used in evaluation. …”
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  12. 12
    Investigation of the optimal sensor location and classifier for human motion classification

    Investigation of the optimal sensor location and classifier for human motion classification by Anuar, Mohamed, Nur Aqilah, Othman, Hamzah, Ahmad, Mohd Hasnun Ariff, Hassan

    Published 2022
    “…In addition, this study seeks to find the best classification algorithm for human daily activities. The data recorded at these three locations were analysed using several classification algorithms in both Orange software and MATLAB. …”
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  13. 13
    An Experimental Study of Classification Algorithms Training Performance

    An Experimental Study of Classification Algorithms Training Performance by Aboalayon, Khald Ali I.

    Published 2005
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  14. 14
    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…However, WKM-SVM has several limitations that are related to k-Means Clustering. …”
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  15. 15
    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…However, WKM-SVM has several limitations that are related to k-Means Clustering. …”
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  16. 16
    Classification of basal stem rot disease in oil palm using dielectric spectroscopy

    Classification of basal stem rot disease in oil palm using dielectric spectroscopy by Al-Khaled, Al-Fadhl Yahya Khaled

    Published 2018
    “…Without implementing any data reduction algorithm, the highest classification accuracy was found in SVM classifier with 79.55%. …”
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  17. 17
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
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  18. 18
    Biceps brachii surface EMG classification using neural networks

    Biceps brachii surface EMG classification using neural networks by Chong, Yee Lin

    Published 2012
    “…The proposed BPN with Levenberg-Marquardt (LM) algorithm and PNN had achieved an overall classification rate of 88% while BPN with Resilient-Propagation (RP) algorithm achieved an overall classification of 87.11%. …”
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  19. 19
    Machine learning classifications of multiple organ failures in a malaysian intensive care unit

    Machine learning classifications of multiple organ failures in a malaysian intensive care unit by Norliyana, Nor Hisham Shah, Normy Norfiza, Abdul Razak, Athirah, Abdul Razak, Asma’, Abu-Samah, Fatanah, M. Suhaimi, Ummu Kulthum, Jamaludin

    Published 2024
    “…This study aims to perform the classification of multiple organ failures using machine learning algorithms based on SOFA score. …”
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  20. 20
    Machine Learning Classifications of Multiple Organ Failures in a Malaysian Intensive Care Unit

    Machine Learning Classifications of Multiple Organ Failures in a Malaysian Intensive Care Unit by Shah N.N.H., Razak N.N.A., Razak A.A., Abu-Samah A., Suhaimi F.M., Jamaluddin U.

    Published 2025
    “…This study aims to perform the classification of multiple organ failures using machine learning algorithms based on SOFA score. …”
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