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  1. 1
    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
    “…A prototype system of brain segmentation is developed by implementing K-Means Clustering algorithm. …”
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  2. 2
    Framework for stream clustering of trajectories based on temporal micro clustering technique

    Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

    Published 2018
    “…This is because, the clustering process which exploits the time window technique creates new micro clusters for some trajectory segments at the start of each time-bin even though these segments are too close (within distance threshold) to the micro clusters at the end of previous time-bin . …”
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  3. 3
    Performance comparison of clustering and thresholding algorithms for tuberculosis bacilli segmentation.

    Performance comparison of clustering and thresholding algorithms for tuberculosis bacilli segmentation. by Mohammad Khusairi, Osman, Mohd Yusoff, Mashor, Prof. Dr., Hasnan, Jaafar

    Published 2013
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  4. 4
    Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images

    Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images by Jabar F.H.A., Ismail W., Salam R.A., Hassan R.

    Published 2024
    Conference Paper
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  5. 5
    Features extraction based on fuzzy clustering and segmentation onto the motion region for medium field surveillance application

    Features extraction based on fuzzy clustering and segmentation onto the motion region for medium field surveillance application by Maliki, Mohamad Nansah, Abu Bakar Al-Attas, Syed Abdul Rahman

    Published 2004
    “…Fuzzy-based clustering algorithm is becoming popular in image processing, especially in image segmentation. …”
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  6. 6
    Cluster approach for auto segmentation of blast in acute leukimia blood slide images

    Cluster approach for auto segmentation of blast in acute leukimia blood slide images by N. H., Harun, Mohd Yusoff, Mashor, Prof. Dr., H., Rosline

    Published 2011
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  7. 7
    Improved Fast Fuzzy C-Means Algorithm for Medical MR Images Segmentation

    Improved Fast Fuzzy C-Means Algorithm for Medical MR Images Segmentation by Li, Min, Huang, Tinglei, Zhu, Gangqiang

    Published 2008
    “…Fuzzy c-means (FCM) clustering algorithm has been widely used in automated image segmentation. …”
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  8. 8
    Customer segmentation using clustering techniques / Mohamad Amir Salihin Mustafa

    Customer segmentation using clustering techniques / Mohamad Amir Salihin Mustafa by Mustafa, Mohamad Amir Salihin

    Published 2024
    “…Customer profiling is the result of the segmentation process. The Silhouette Score is used to assess the quality of the clustering model, and it achieves a good value of 0.54. …”
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  9. 9
    Segmentation of MRI brain images using statistical approaches

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

    Published 2011
    “…The Gaussian Mixture Model (GMM) is a clustering algorithm that is commonly used for brain MRI segmentation. …”
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  10. 10
    K-Means Clustering Approach for Intelligent Customer Segmentation Using Customer Purchase Behavior Data

    K-Means Clustering Approach for Intelligent Customer Segmentation Using Customer Purchase Behavior Data by Kayalvily, Tabianan, Shubashini, Velu, VInayakumar, Ravi

    Published 2022
    “…It also enables high exposure of the e-offer to gain attention of potential customers. In order to process the collected data and segment the customers, an learning algorithm is used which is known as K-Means clustering. …”
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  11. 11
    A survey: Challenges of image segmentation based fuzzy c-means clustering algorithm

    A survey: Challenges of image segmentation based fuzzy c-means clustering algorithm by Alomoush W., Alrosan A., Norwawi N., Alomari Y., Albashish D., Almomani A., Alqahtani M.

    Published 2024
    journal::journal article
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  12. 12
    MRI segmentation of medical images using FCM with initialized class centers via genetic algorithm

    MRI segmentation of medical images using FCM with initialized class centers via genetic algorithm by Balafar, Mohammad Ali, Ramli, Abdul Rahman, Saripan, M. Iqbal, Mahmud, Rozi, Mashohor, Syamsiah, Balafar, Hakimeh

    Published 2008
    “…Image segmentation is a critical stage in many computer vision and image process applications. …”
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    Conference or Workshop Item
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  13. 13
    Quantification and segmentation of breast cancer diagnosis: efficient hardware accelerator approach

    Quantification and segmentation of breast cancer diagnosis: efficient hardware accelerator approach by Othman, Khairulnizam

    Published 2022
    “…Segmentation clustering algorithms have setbacks on overlapping clusters, proportion, and multidimensional scaling to map and leverage the data. …”
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  14. 14
    Image Segmentation Using an Adaptive Clustering Technique for the Detection of Acute Leukemia Blood Cells Images

    Image Segmentation Using an Adaptive Clustering Technique for the Detection of Acute Leukemia Blood Cells Images by Jabar, FHA, Ismail, W, Salam, RA, Hassan, R

    Published 2024
    “…This paper aims to segment the blood cell images of patients suffering from acute leukemia using an adaptive K-Means clustering together with mean shift algorithm. …”
    Proceedings Paper
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  15. 15
    Development of Acute Stroke Lesion Segmentation Algorithm in Brain MRI using Pseudo-colour with K-means Clustering

    Development of Acute Stroke Lesion Segmentation Algorithm in Brain MRI using Pseudo-colour with K-means Clustering by Abang Mohd Arif Anaqi, Abang Isa

    Published 2021
    “…This study aims to develop an automatic segmentation by utilizing clustering algorithm for acute ischemic stroke lesion identification. …”
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  16. 16
    Image Segmentation using Enhanced K-means Clustering with Hybrid Image Filtering for Acute Leukemia Blood Cells Microscopic Images

    Image Segmentation using Enhanced K-means Clustering with Hybrid Image Filtering for Acute Leukemia Blood Cells Microscopic Images by Farah Hanim Bt Abd Jabar

    Published 2024
    thesis::master thesis
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  17. 17
    Effects of Different Superpixel Algorithms on Interactive Segmentations

    Effects of Different Superpixel Algorithms on Interactive Segmentations by Soo See, Chai, Luong Goh, Kok, Weng Ng, Giap, Muzaffar, Hamzah

    Published 2022
    “…Though employed as pre-processing step in many interactive segmentation algorithms, to date, no study has been conducted to assess the effects of such incorporations on the segmentation algorithms. …”
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  18. 18
    Pengesanan nombor plat kenderaan menggunakan alkhwarizmi gugusan dan kelancaran jarak larian(GKJL)

    Pengesanan nombor plat kenderaan menggunakan alkhwarizmi gugusan dan kelancaran jarak larian(GKJL) by Siti Norul Huda Sheikh Abdullah, Marzuki Khalid, Khairuddin Omar, Rubiyah Yusof

    Published 2009
    “…CRLSA consists of two separate proposed algorithm which applied proposed edge detector algorithm using 3×3 kernel masks and 128 grayscale offset, and the resulting image is thresholded in order to calculate Run Length Smoothing Algorithm (RLSA), which has shown to improve the clustering process in the segmentation phase. …”
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  19. 19
    Drone Based Image Processing For Precision Agriculture

    Drone Based Image Processing For Precision Agriculture by Sharif, Muhammad Arif Syafiq Md

    Published 2019
    “…Post K-means clustering, the diseased portions of the plants were assessed using Hue-Saturation-Value (HSV) based image segmentation algorithm. …”
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    Monograph
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  20. 20
    Effects of Different Superpixel Algorithms on Interactive Segmentations

    Effects of Different Superpixel Algorithms on Interactive Segmentations by Goh, Kok Luong, Ng, Giap Weng, Muzaffar Hamzah, Chai, Soo See

    Published 2022
    “…Though employed as pre-processing step in many interactive segmentation algorithms, to date, no study has been conducted to assess the effects of such incorporations on the segmentation algorithms. …”
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