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  1. 1
    Image segmentation based on normalised cuts with clustering algorithm

    Image segmentation based on normalised cuts with clustering algorithm by Choong, Mei Yeen

    Published 2013
    “…Clustered segments from the local segmentation are then used for image segmentation in global perspective. …”
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  2. 2
    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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  3. 3
    Customer segmentation on clustering algorithms

    Customer segmentation on clustering algorithms by Toh, Wei Xuan

    Published 2023
    “…Then, k-means, DBSCAN, and GMM clustering algorithms are applied to segment customers based on their buying behaviour. …”
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  4. 4
    Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation

    Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation by Alia, Osama Moh’d Radi

    Published 2011
    “…Fuzzy clustering algorithms, which fall under unsupervised machine learning, are among the most successful methods for image segmentation. …”
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  5. 5
    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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  6. 6
    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
    “…The temporal micro cluster data structure is proposed in CC_TRS algorithm to store the summarized information for each group of similar segments. …”
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  7. 7
    Unsupervised segmentation technique for acute leukemia cells using clustering algorithms

    Unsupervised segmentation technique for acute leukemia cells using clustering algorithms by Harun, Nor Hazlyna, Abdul Nasir, Aimi Salihah, Mashor, Mohd Yusoff, Hassan, Rosline

    Published 2015
    “…Then, median filter and seeded region growing area extraction algorithms have been applied, to smooth the region of segmented blast and to remove the large unwanted regions from the image, respectively.Comparisons among the three clustering algorithms are made in order to measure the performance of each clustering algorithm on segmenting the blast area. …”
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  8. 8
    Harmony search-based fuzzy clustering algorithms for image segmentation.

    Harmony search-based fuzzy clustering algorithms for image segmentation. by Alia, Osama Moh’d Radi

    Published 2011
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  9. 9
    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
    “…This study explores clustering techniques for customer segmentation, focusing on the K-Means algorithm in particular, and uses a dataset that was obtained from the customer data of an international supermarket company. …”
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  10. 10
    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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  11. 11
    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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  12. 12
    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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  13. 13
    Pseudo-colour with K-means Clustering Algorithm for Acute Ischemic Stroke Lesion Segmentation in Brain MRI

    Pseudo-colour with K-means Clustering Algorithm for Acute Ischemic Stroke Lesion Segmentation in Brain MRI by Abang Mohd Arif Anaqi, Abang Isa, Kuryati, Kipli, Ahmad Tirmizi, Jobli, Muhammad Hamdi, Mahmood, Siti Kudnie, Sahari, Aditya Tri, Hernowo, Sinin, Hamdan

    Published 2021
    “…This paper presented an automated segmentation algorithm on diffusion-weighted magnetic resonance imaging (DW-MRI) image utilizing pseudo-colour conversion and K-means clustering techniques. …”
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  14. 14
    Blood cell image segmentation using unsupervised clustering techniques

    Blood cell image segmentation using unsupervised clustering techniques by Tuan Muda, Tuan Zalizam, Abdul Salam, Rosalina

    Published 2009
    “…Results from the segmented cell will be use for further classification and recognition.…”
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    Conference or Workshop Item
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  15. 15
    AUTOMATED CERVICAL CELL NUCLEI SEGMENTATION BASED ON MULTILAYER UNSUPERVISED CLUSTERING ALGORITHM AND MORPHOLOGICAL APPROACH

    AUTOMATED CERVICAL CELL NUCLEI SEGMENTATION BASED ON MULTILAYER UNSUPERVISED CLUSTERING ALGORITHM AND MORPHOLOGICAL APPROACH by Khalis Danial Nukman, Khiruddin, Wan Azani, Mustafa, Khairur Rijal, Jamaludin, Khairul Shakir, Ab Rahman, Hiam, Alquran, Syahrul Nizam, Junaini

    Published 2025
    “…The research aims to develop an algorithm for autonomously segmenting the nucleus of cervical cells to aid in diagnosis and future research. …”
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  16. 16
    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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  17. 17
    Cluster validity of Xie and Beni and the partition coefficient indexes for fuzzy c-means clustering / Nor Azrin Ahmad Mustaffa

    Cluster validity of Xie and Beni and the partition coefficient indexes for fuzzy c-means clustering / Nor Azrin Ahmad Mustaffa by Ahmad Mustaffa, Nor Azrin

    Published 2010
    “…Segmentation defines the boundary of the targeted object from its background in the images. …”
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  18. 18
    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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  19. 19
    A study of left ventricular (LV) segmentation on cardiac cine-MR images

    A study of left ventricular (LV) segmentation on cardiac cine-MR images by Ahad, Md Atiqur Rahman, Jahan, Israt

    Published 2022
    “…Both adaptive and global thresholding algorithms along with region-based segmentation algorithm have been explored. …”
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  20. 20
    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
    “…Semi-automated segmentation or more commonly known as interactive image segmentation is an algorithm that extracts a region of interest (ROI) from an image based on the input information from the user. …”
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