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  1. 1
    An improved public key cryptography based on the elliptic curve

    An improved public key cryptography based on the elliptic curve by Al-Daoud, Essam Faleh

    Published 2002
    “…To speed up the underlying finite field operations, several new algorithms are introduced namely: selecting random sparse elements algorithm, finding sparse base points, sparse multiplication over polynomial basis, and sparse multiplication over normal basis. …”
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  2. 2
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
    “…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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  3. 3
    An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding

    An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding by Safa, Soodabeh, Khalid, Fatimah

    Published 2020
    “…Moreover, sparse coding has been commonly used in recent years for the purposes of retrieving and identifying images. …”
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  4. 4
    Evaluation of sparsifying algorithms for speech signals

    Evaluation of sparsifying algorithms for speech signals by Kassim, Liban A., Khalifa, Othman Omran, Gunawan, Teddy Surya

    Published 2012
    “…Sparse representations of signals have been used in many areas of signal and image processing. …”
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    Proceeding Paper
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  5. 5
    BRAIN SOURCE LOCALIZATION TECHNIQUE FOR EEG SIGNALS BASED ON ENHANCED MULTIPLE SPARSE PRIORS

    BRAIN SOURCE LOCALIZATION TECHNIQUE FOR EEG SIGNALS BASED ON ENHANCED MULTIPLE SPARSE PRIORS by MUNSIF, ALI JATOI

    Published 2017
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  6. 6
    Compressed Sensing Implementations For Sparse Channel Estimation In OFDM Systems

    Compressed Sensing Implementations For Sparse Channel Estimation In OFDM Systems by Uwaechia, Anthony Ngozichukwuka

    Published 2018
    “…Hence, a new fusion framework namely, Collaborative Framework of Algorithms (CoFA) is proposed, to pursue accurate recovery of the sparse signals from few linear measurements. …”
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  7. 7
    Rain streaks removal using total variation and sparse coding based on case based reasoning approach

    Rain streaks removal using total variation and sparse coding based on case based reasoning approach by Shorman S.M., Salam R.A., Sakinah Ali Pitchay

    Published 2024
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  8. 8
    Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification

    Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification by Mohammed, Alhassan Afnan

    Published 2022
    “…Then, the selected features are given as input to the DBN classifier which is trained using the Taylor-based bird swarm algorithm (Taylor-BSA). …”
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  9. 9
    Removing mixture of Gaussian and Impulse noise of images using sparse coding

    Removing mixture of Gaussian and Impulse noise of images using sparse coding by Mahsa Malekzadeh, Saeed Meshgini, Reza Afrouzian, Ali Farzamnia, Sobhan Sheykhivand

    Published 2020
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  10. 10
    Blind Source Separation Using Two-Dimensional Nonnegative Matrix Factorization In Biomedical Field

    Blind Source Separation Using Two-Dimensional Nonnegative Matrix Factorization In Biomedical Field by Toh, Cheng Chuan

    Published 2018
    “…Theoretically,β and α is parameters that used to vary the NMF2D algorithm in order to yield high SDR value. …”
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  11. 11
    Scene classification for aerial images based on CNN using sparse coding technique

    Scene classification for aerial images based on CNN using sparse coding technique by Qayyum, A., Malik, A.S., Saad, N.M., Iqbal, M., Faris Abdullah, M., Rasheed, W., Rashid Abdullah, T.A., Bin Jafaar, M.Y.

    Published 2017
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  12. 12
    Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach

    Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach by Qayyum A., Saeed Malik A., Saad N.M., Iqbal M., Abdullah M.F., Rasheed W., Abdullah T.A.B.R., Bin Jafaar M.Y.

    Published 2023
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  13. 13
    An Educational Tool Aimed at Learning Metaheuristics

    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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  14. 14
    Visual Simultaneous Localization and Mapping Using Direct-Based Method for Unmanned Aerial Vehicle (UAV)

    Visual Simultaneous Localization and Mapping Using Direct-Based Method for Unmanned Aerial Vehicle (UAV) by M. H., Badzli, N., Mohamad Yatim, A., Jamaludin, Z., Mohd Noh, M. I., Idris, N. A., Sulaiman, Nur Aqilah, Othman

    Published 2023
    “…The Direct Sparse Odometry (DSO) technique is a new form of visual odometry that makes use of a direct and sparse structure to achieve precision. …”
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  15. 15
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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  16. 16
    Image denoising using combined higher order non-convex total variation with overlapping group sparsity

    Image denoising using combined higher order non-convex total variation with overlapping group sparsity by Adam, Tarmizi, Paramesran, Raveendran

    Published 2019
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  17. 17
    Prime-based method for interactive mining of frequent patterns

    Prime-based method for interactive mining of frequent patterns by Nadimi-Shahraki, Mohammad-Hossein

    Published 2010
    “…Since rerunning the mining algorithms from scratch can be very time consuming, researchers have introduced interactive mining to find proper patterns by using the current mining model with various minsup. …”
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  18. 18
    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment

    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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  19. 19
    Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman

    Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman by Seman, Ali

    Published 2013
    “…In some cases, they are quite distant and sparseness. This uniqueness of Y-STR data has become problematic in partitioning the data using the existing partitional clustering algorithms. …”
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  20. 20
    Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification

    Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification by Sobhan Sheykhivand, Tohid Yousefi Rezaii, Zohreh Mousavi, Azra Delpak, Ali Farzamnia

    Published 2020
    “…In this research, a fully automated system is presented to automatically detect the various states of the epileptic seizure. This study is based on sparse representation-based classification (SRC) theory and the proposed dictionary learning using electroencephalogram (EEG) signals. …”
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