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  1. 1
    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
    “…In the classic Bag of visual words model, the Fuzzy c-means algorithm is replaced with K-means and the accuracy of SIFT matching is increased. …”
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  2. 2
    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…In cluster labelling process, a cluster labelling algorithm based on calculation of minimum-distance (MD) between cluster mean and class mean was developed to label the clusters. …”
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  3. 3
    Visualization of dengue incidences using expectation maximization (EM) algorithm

    Visualization of dengue incidences using expectation maximization (EM) algorithm by Mathur, N., Asirvadam, V.S., Dass, S.C., Gill, B.S.

    Published 2017
    “…Along with the prediction modeling on data using centroid model and distribution model based on K-means and Expectation Maximization (EM) algorithms respectively. …”
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  4. 4
    Implementation of Parallel K-Means Algorithm to Estimate Adhesion Failure in Warm Mix Asphalt

    Implementation of Parallel K-Means Algorithm to Estimate Adhesion Failure in Warm Mix Asphalt by Akhtar, M.N., Ahmed, W., Kakar, M.R., Bakar, E.A., Othman, A.R., Bueno, M.

    Published 2020
    “…The results showed that the PKIP algorithm decreases the execution time up to 30 to 46 if compared with the sequential k means algorithm when implemented using multiprocessing and distributed computing. …”
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  5. 5
    GMSD-based perceptually motivated non-local means filter for image denoising

    GMSD-based perceptually motivated non-local means filter for image denoising by Baqar, Mohtashim *, Lau, Sian Lun *

    Published 2019
    “…Further, the proposed methodology also helps in mitigating the patch jittering blur effect (PJBE) and over smoothing of denoised images as observed with conventional NLM algorithm. Experimental evaluations based on visual-quality assessment and least-square based metrics have shown that the proposed algorithm yields better denoised image estimates than the conventional NLM algorithm. …”
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  6. 6
    K-means clustering and visualizing of significant words prototype for crowdsourced relationship comments / Muhammad Syafiq Mastor

    K-means clustering and visualizing of significant words prototype for crowdsourced relationship comments / Muhammad Syafiq Mastor by Mastor, Muhammad Syafiq

    Published 2015
    “…The comments are clustered using K-Means algorithm and visualized using scatter plot. …”
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  7. 7
    Tag cloud algorithm with the inclusion of personality traits

    Tag cloud algorithm with the inclusion of personality traits by Supli, Ahmad Affandi, Shiratuddin, Norshuhada, Ab. Aziz, Azizi

    Published 2014
    “…Since there is no study has tried to create an algorithm that can customize tag cloud visual properties based on personality traits. …”
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  8. 8
    Investigation And Development Of Forensic Mean-Based Adaptive Background Correction Algorithm (Mabca) For Visual Enhancement Of Bloodstains, Seminal Stains And Fingerprints

    Investigation And Development Of Forensic Mean-Based Adaptive Background Correction Algorithm (Mabca) For Visual Enhancement Of Bloodstains, Seminal Stains And Fingerprints by Lee, Wee Chuen

    Published 2017
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  9. 9
    Modified Contrast Limited Adaptive Histogram Equalization for high dynamic range images

    Modified Contrast Limited Adaptive Histogram Equalization for high dynamic range images by Tung, Li Qian

    Published 2012
    “…As a result, a fully automatic local tone mapping algorithm was introduced to increase the local contrast and reduce the loss of visual visibility. …”
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  10. 10
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

    Published 2023
    “…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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  11. 11
    Visualisasi pohon sintaksis berasaskan model dan algoritma sintaks ayat bahasa Melayu

    Visualisasi pohon sintaksis berasaskan model dan algoritma sintaks ayat bahasa Melayu by Yusnita, Muhamad Noor

    Published 2018
    “…It can be concluded that the algorithm and model proposed were useful for the development of the prototype. …”
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  12. 12
    K-means Clustering Analysis for EEG Features of Situational Interest Detection in Classroom Learning

    K-means Clustering Analysis for EEG Features of Situational Interest Detection in Classroom Learning by Othman, E.S., Faye, I., Babiker, A., Hussaan, A.M.

    Published 2021
    “…Electroencephalogram (EEG) signal was preprocessed and decomposed using Fast Fourier Transform. The mean power for each sub-frequency band was served as input to the k-means algorithm. …”
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  13. 13
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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  14. 14
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majid Khan bin Majahar Ali, Majid Khan bin Majahar Ali

    Published 2023
    “…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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  15. 15
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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  16. 16
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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  17. 17
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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  18. 18
    OCR Signage Recognition with Skew & Slant Correction For Visually Impaired People

    OCR Signage Recognition with Skew & Slant Correction For Visually Impaired People by Hairuman, Intan Fariza, Foong, Oi-Mean

    Published 2012
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  19. 19
    OCR Signage Recognition with Skew & Slant Correction For Visually Impaired People

    OCR Signage Recognition with Skew & Slant Correction For Visually Impaired People by Hairuman, Intan Fariza Bt, Foong, Oi Mean

    Published 2011
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  20. 20
    CNN-SVO: improving the mapping in semi-direct visual odometry using single-image depth prediction

    CNN-SVO: improving the mapping in semi-direct visual odometry using single-image depth prediction by Loo, Shing Yan, Amiri, Ali Jahani, Mashohor, Syamsiah, Tang, Sai Hong, Zhang, Hong

    Published 2019
    “…Reliable feature correspondence between frames is a critical step in visual odometry (VO) and visual simultaneous localization and mapping (V-SLAM) algorithms. …”
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