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  1. 1
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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  2. 2
    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
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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  3. 3
    Development of seven segment display recognition using TensorFlow on Raspberry Pi

    Development of seven segment display recognition using TensorFlow on Raspberry Pi by Gunawan, Teddy Surya, Mohammad Reduwan, Haque, Yaacob, Mashkuri, Mohamed Azmin, Nor Fadhillah, Ismail, Nanang, Ismail, Md Yusof, Kartiwi, Mira, A. Rahman, Azhar

    Published 2022
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  4. 4
    Optimized clustering with modified K-means algorithm

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…The proposed algorithm utilised a distance measure to compute the between groups’ separation to accelerate the process of identifying an optimal number of clusters using k-means. …”
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  5. 5
    Using a novel algorithm in ultrasound images to detect renal stones

    Using a novel algorithm in ultrasound images to detect renal stones by Sania Eskandari, Saeed Meshgini, Ali Farzamnia

    Published 2021
    “…Fuzzy C-means, K-means, and Expectation–Maximization algorithms are used to segment the renal calculi from the kidney ultrasound image; further region parameters are extracted from the segmented region. …”
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    Proceedings
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  6. 6
    Widely linear dynamic quaternion valued least mean square algorithm for linear filtering

    Widely linear dynamic quaternion valued least mean square algorithm for linear filtering by Mohammed, Aldulaimi Haydar Imad

    Published 2017
    “…The new adaptive algorithm is called dynamic quaternion least mean square algorithm (DQLMS) because of the normalization process of the filter input and the variable step-size. …”
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  7. 7
    Adaptive interference canceller using analog algorithm with offset voltage

    Adaptive interference canceller using analog algorithm with offset voltage by Mohammed, Alaa Hadi

    Published 2015
    “…LMS and NLMS algorithms have been used in a wide range of signal processing applications because of their simplicity in computations compared to the RLS algorithm. …”
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  8. 8
    Elucidating the effect of process parameters on the production of hydrogen-rich syngas by biomass and coal Co-gasification techniques: A multi-criteria modeling approach

    Elucidating the effect of process parameters on the production of hydrogen-rich syngas by biomass and coal Co-gasification techniques: A multi-criteria modeling approach by Bahadar A., Kanthasamy R., Sait H.H., Zwawi M., Algarni M., Ayodele B.V., Cheng C.K., Wei L.J.

    Published 2023
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  9. 9
    Extracting feature from images by using K-Means clustering algorithm / Abdul Hakim Zainal Abidin

    Extracting feature from images by using K-Means clustering algorithm / Abdul Hakim Zainal Abidin by Zainal Abidin, Abdul Hakim

    Published 2016
    “…This research purposed clustering algorithm to improve process extracting feature in images to get meaningful information because it can speed up the time to process of extracting meaningful information in images due to the efficient of the algorithm that has high performance to process the image. …”
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  10. 10
    Malaria parasites segmentation in red blood cells images using mean-shift and median-cut

    Malaria parasites segmentation in red blood cells images using mean-shift and median-cut by Tn. Muda, Tn. Zalizam, A Salam, Rosalina

    Published 2010
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  11. 11
    Improved clustering using robust and classical principal component

    Improved clustering using robust and classical principal component by Hassn, Ahmed Kadom

    Published 2017
    “…The classical k-means algorithm and the k-means by PCA algorithm are very sensitive to the presence of outlier. …”
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  12. 12
    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm

    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

    Published 2025
    “…After classifying the time set using the canopy with the K-means algorithm and the vector representation weighted by factors, the clustering impact is assessed using purity, precision, recall, and F value. …”
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  13. 13
    Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor

    Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor by Abu Mangshor, Nur Nabilah

    Published 2010
    “…This project is about segmentation of FLAIR brain Magnetic Resonance Image (MRI) using K-Means Clustering algorithm. A prototype system of brain segmentation is developed by implementing K-Means Clustering algorithm. …”
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  14. 14
    Tracking The Eyes Using Interdependence Mean Shift Tracking Algorithm With Appropriate Information Provided

    Tracking The Eyes Using Interdependence Mean Shift Tracking Algorithm With Appropriate Information Provided by Masrullizam, Mat Ibrahim, Syafeeza, Ahmad Radzi, Soraghan, John

    Published 2016
    “…Most of the developed eyes tracking algorithm are not considered the condition of the eyes that would provide the appropriate information to be used in the processes of the facial analysis algorithm. …”
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  15. 15
    Segmentation of MRI brain images using statistical approaches

    Segmentation of MRI brain images using statistical approaches by Balafar, Mohammad Ali

    Published 2011
    “…Therefore, these algorithms can be improved upon. A neighbourhood-based noise-reduction algorithm which uses the edges of an image is proposed. …”
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  16. 16
    An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title

    An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title by Khalaf, Emad Taha

    Published 2019
    “…The enhanced method combines three transformation methods for analyzing the iris image and extracting its local features. It uses a weighted K-means clustering algorithm based on the improved FA to optimize the initial clustering centers of K-means algorithm, known as Weighted K-means clustering-Improved Firefly Algorithm (WKIFA). …”
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  17. 17
    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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  18. 18
    Pattern discovery using k-means algorithm

    Pattern discovery using k-means algorithm by Ahmed, Almahdi Mohammed, Wan Ishak, Wan Hussain, Md Norwawi, Norita, Alkilany, Ahmed

    Published 2014
    “…This paper will discuss the results of a pattern extraction process using a clustering algorithm that is k-means. …”
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    Conference or Workshop Item
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  19. 19
    loformation Retrieval - using Porter Stemming Algorithm

    loformation Retrieval - using Porter Stemming Algorithm by Zulkifly, Zurida Azita

    Published 2006
    “…The rationale for using stemming is that similar words usually have similar meanings, so including words that are similar in meaning to those originally contained within it will increased the retrieval process effectiveness. …”
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  20. 20
    Comparative analysis of K-Means and K-Medoids for clustering exam questions / Nurul Zafirah Mokhtar

    Comparative analysis of K-Means and K-Medoids for clustering exam questions / Nurul Zafirah Mokhtar by Mokhtar, Nurul Zafirah

    Published 2016
    “…K-Means and k-Medoids are popular technique used in the world of clustering. …”
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