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  1. 1
    Image classification using two dimensional wavelet coefficients with parallel computing

    Image classification using two dimensional wavelet coefficients with parallel computing by Ong, Yew Fai

    Published 2020
    “…The low-level features such as edges, blobs, and ridges were extracted for grouping and classification. Object recognition and image classification comes after the wavelet transform. …”
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  2. 2
    Robust partitioning and indexing for iris biometric database based on local features

    Robust partitioning and indexing for iris biometric database based on local features by Khalaf, Emad Taha, Mohammed, Muamer N., Kohbalan, Moorthy

    Published 2018
    “…Further, the scalable K-means++ algorithm is used for partitioning and classification processes, and an efficient parallel technique that divides the features groups causing the formation of two b-trees based on index keys is applied for search and retrieval. …”
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  3. 3
    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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  4. 4
    Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui

    Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui by Muhammad Faisal , Siddiqui

    Published 2016
    “…Parallel imaging is a robust method for accelerating the data acquisition in Magnetic Resonance Imaging (MRI). …”
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  5. 5
    Parallel implementation of genomic sequences classification using modified gabor wavelet transform on multicore systems

    Parallel implementation of genomic sequences classification using modified gabor wavelet transform on multicore systems by Gunawan, Teddy Surya, Ambikairajah, Eliathamby

    Published 2012
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  6. 6
    Parallel execution of distributed SVM using MPI (CoDLib)

    Parallel execution of distributed SVM using MPI (CoDLib) by Salleh N.S.M., Suliman A., Ahmad A.R.

    Published 2023
    “…Instead of using a single machine for parallel computing, multiple machines in a cluster are used. …”
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  7. 7
    Intelligent classification algorithms in enhancing the performance of support vector machine

    Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2019
    “…Eight benchmark datasets from UCI were used in the experiments to validate the performance of the proposed algorithms. …”
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  8. 8
    The forecasting of poverty using the ensemble learning classification methods

    The forecasting of poverty using the ensemble learning classification methods by Zamzuri, Muhammad Haziq Adli, Nadilah, Sofian, Hassan, Raini

    Published 2023
    “…This research was conducted to forecast poverty using classification methods. Random Forest and Extreme Gradient Boosting (XGBoost) algorithms were applied to forecast poverty since they are supervised learning algorithms that use the ensemble learning approach for classification. …”
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  9. 9
    Text classification using Naive Bayes: An experiment to conference paper

    Text classification using Naive Bayes: An experiment to conference paper by Sainin, Mohd Shamrie

    Published 2005
    “…The basic text classification technique in forum application has been discussed in Sainin (2005a) and Sainin (2005b).The paper explains about the use of the basic naïve Bayes algorithm to classify forum text me ssages into two classes namely clean and bad. …”
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  10. 10
    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms

    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

    Published 2015
    “…This was achieved by mitigating convergence in the genetic algorithms by employing a hierarchical parallel architecture. …”
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  11. 11
    Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System

    Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

    Published 2020
    “…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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  12. 12
    CUDA implementation of fractal image compression

    CUDA implementation of fractal image compression by Al Sideiri A., Alzeidi N., Al Hammoshi M., Chauhan M.S., AlFarsi G.

    Published 2023
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  13. 13
    Parallel implementation of genomic sequences classification using modified Gabor wavelet transform on multicore systems

    Parallel implementation of genomic sequences classification using modified Gabor wavelet transform on multicore systems by Gunawan, Teddy Surya, Ambikairajah, Eliathamby

    Published 2012
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  14. 14
    Design and analysis of management platform based on financial big data

    Design and analysis of management platform based on financial big data by Chen, Yuhua, Mustafa, Hasri, Zhang, Xuandong, Liu, Jing

    Published 2023
    “…In addition, a financial data management platform based on distributed Hadoop architecture is designed, which combines MapReduce framework with the fuzzy clustering algorithm and the local outlier factor (LOF) algorithm, and uses MapReduce to operate in parallel with the two algorithms, thus improving the performance of the algorithm and the accuracy of the algorithm, and helping to improve the operational efficiency of enterprise financial data processing. …”
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  15. 15
    Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living

    Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living by Hamza, Manar Ahmed, Hassan Abdalla Hashim, Aisha, Motwakel, Abdelwahed, Elhameed, Elmouez Samir Abd, Osman, Mohammed, Kumar, Arun, Singla, Chinu, Munjal, Muskaan

    Published 2024
    “…Natural Language Processing (NLP) with Deep Learning (DL) for Tweets Classification includes use of advanced neural network designs to analyse and classify Twitter messages. …”
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  16. 16
    An Improve k-NN Classifier using Similarity Distance Plot-Data Reduction and Dask for Big Datasets

    An Improve k-NN Classifier using Similarity Distance Plot-Data Reduction and Dask for Big Datasets by Abdul Muqtasid, Rushdi

    Published 2025
    “…The k-Nearest Neighbour (k-NN) algorithm is one of the most widely used Instance-Based Learning methods due to its simplicity and ease of implementation. …”
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  17. 17
    A block-based multi-scale background extraction algorithm

    A block-based multi-scale background extraction algorithm by Davarpanah, Seyed Hashem, Khalid, Fatimah, Golchin, Maryam

    Published 2010
    “…Approach: In this study, to extract an adaptive background, a combination of blocking and multi-scale methods is presented. …”
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  18. 18
    EMG motion pattern classification through design and optimization of neural network

    EMG motion pattern classification through design and optimization of neural network by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

    Published 2012
    “…Extracted time and time-frequency based feature sets are used to train the neural network. A back-propagation neural network with Levenberg-Marquardt training algorithm has been utilized for the classification of EMG signals. …”
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  19. 19
    Genetic algorithm based ensemble framework for sentiment analysis

    Genetic algorithm based ensemble framework for sentiment analysis by Lai, Po Hung

    Published 2018
    “…Prior to developing the whole multilayered ensemble framework, two separate experiments were performed to evaluate and study the different methods of feature extraction and selection. Methods of feature extraction can be separated into word based and phrase based. …”
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  20. 20
    VLSI Design of a neurohardware processor implementing the Kohonen Neural Network algorithm

    VLSI Design of a neurohardware processor implementing the Kohonen Neural Network algorithm by Rajah, Avinash

    Published 2005
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