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  1. 1
    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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  2. 2
    Color video denoising using epitome and sparse coding

    Color video denoising using epitome and sparse coding by Lee, H.Y., Hoo, W.L., Chan, C.S.

    Published 2015
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  3. 3
    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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  4. 4
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…Today, with online marketing, banking, healthcare and other services, even the average householder is aware of encryption. The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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  5. 5
    An improved self organizing map using jaccard new measure for textual bugs data clustering

    An improved self organizing map using jaccard new measure for textual bugs data clustering by Ahmed, Attika

    Published 2018
    “…The research results suggested that SOM has a limitation of poor performance on sparse data set. Thus, the research introduced the improved SOM algorithm by using a Jaccard NM (SOM-JNM). …”
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  6. 6
    An improved self organizing map using jaccard new measure for textual bugs data clustering

    An improved self organizing map using jaccard new measure for textual bugs data clustering by Ahmed, Attika

    Published 2018
    “…The research results suggested that SOM has a limitation of poor perfonnance on sparse data set. Thus, the research introduced the improved SOM algorithm by using a Jaccard NM (SOM-JNM). …”
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  7. 7
    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 feature selection process is performed using sparse fuzzy-c-means (FCM) for selecting significant features to classify medical data. …”
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  8. 8
    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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  9. 9
    Speech compression using compressive sensing on a multicore system

    Speech compression using compressive sensing on a multicore system by Gunawan, Teddy Surya, Khalifa, Othman Omran, Shafie, Amir Akramin, Ambikairajah, Eliathamby

    Published 2011
    “…Finally, to speed up the process, the proposed algorithm will be implemented in a multicore system, i.e. six cores, using Single Program Multiple Data (SPMD) parallel paradigm.…”
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  10. 10
    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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  11. 11
    Provider independent cryptographic tools

    Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

    Published 2003
    “…The library is implemented by using Java cryptographic service provider framework that conforms to Java Cryptographic Architecture (JCA) and Java Cryptographic Extension (JCE). …”
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    Monograph
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  12. 12
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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  13. 13
    AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING

    AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING by SALLEH AL-HUMAIKANI, MOHAMMED ABDULQAWI

    Published 2021
    “…RSA is one of these encryption algorithms that have been implemented in security systems. …”
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  14. 14
    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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  15. 15
    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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  16. 16
    A multilayered convolutional sparse coding framework for modeling of pooling operation of convolution neural networks

    A multilayered convolutional sparse coding framework for modeling of pooling operation of convolution neural networks by , Abdul Wahid, Khan, Adnan Umar, , Mukhtarullah, Khan, Sheroz, Shah, Jawad

    Published 2019
    “…The multilayered version of CSC(ML-CSC) is shown to be connected to forward pass of CNNs and dictionary learning and sparse coding algorithms of this model are analyzed for solving classification and inverse problems in image processing. …”
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  17. 17
    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
    “…We hyave used the CPU profiler of Oracle JavaTM VisualVM to monitor the execution of LRE-TL as well as USG algorithms. …”
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  18. 18
    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
    “…The main challenges of implementing ANPR algorithm on mobile phone are how to produce a higher coding efficiency, lower computational complexity, and higher scalability. …”
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    Book
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  19. 19
    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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  20. 20
    Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation

    Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation by Chen, Qipeng, Xiong, Qiaoqiao, Huang, Haisong, Tang, Saihong, Liu, Zhenghong

    Published 2024
    “…Channel pruning and layer pruning are applied to the sparse model, and post-processing methods using knowledge distillation are used to effectively reduce the model size and forward inference time while maintaining model accuracy. …”
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