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  1. 1
    Comparative Analysis on Blood Cell Image Segmentation

    Comparative Analysis on Blood Cell Image Segmentation by Muda, TZT, Salam, RA

    Published 2024
    Proceedings Paper
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  2. 2
    Comparative analysis on blood cell image segmentation

    Comparative analysis on blood cell image segmentation by Tuan Muda, Tuan Zalizam, Abdul Salam, Rosalina

    Published 2013
    “…K-means has been enhanced by integrating Median-cut algorithm to further improve the segmentation process.The proposed integrated method has shown a significant improvement in the number of selected regions.…”
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  3. 3
    Adaptive Hybrid Blood Cell Image Segmentation

    Adaptive Hybrid Blood Cell Image Segmentation by Muda, TZT, Salam, RA, Ismail, S

    Published 2024
    Proceedings Paper
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  4. 4
    Adaptive Hybrid Blood Cell Image Segmentation

    Adaptive Hybrid Blood Cell Image Segmentation by Tuan Muda, Tuan Zalizam, Abdul Salam, Rosalina, Ismail, Suzilah

    Published 2019
    “…In this paper, we present an adaptive hybrid analysis based on selected segmentation algorithms. Three designates common approaches, that are Fuzzy c-means, K-means and Mean-shift are adapted. …”
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  5. 5
    Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients

    Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

    Published 2017
    “…In the case of liver tumor segmentation, with a mean overlap error of 19.6% and mean absolute relative volume difference of 11.2%. …”
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  6. 6
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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  7. 7
    Image clustering comparison of two color segmentation techniques

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

    Published 2010
    “…This project proposed a two color segmentation techniques such as K-means and Fuzzy C-means clustering algorithm that are accurately segment the desired images, which have the same color as the pre-selected pixels with background subtraction. …”
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  8. 8
    A hyper-heuristic based strategy for image segmentation using multilevel thresholding

    A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

    Published 2025
    “…Among others, multilevel thresholding is a robust and most widely adopted image segmentation approach. To find the optimal multilevel threshold values, various heuristic and meta-heuristic algorithms have been applied to segment COVID-19 medical images. …”
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  9. 9
    A hyper-heuristic based strategy for image segmentation using multilevel thresholding

    A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

    Published 2025
    “…Among others, multilevel thresholding is a robust and most widely adopted image segmentation approach. To find the optimal multilevel threshold values, various heuristic and meta-heuristic algorithms have been applied to segment COVID-19 medical images. …”
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  10. 10
    Model-based hybrid variational level set method applied to lung cancer detection

    Model-based hybrid variational level set method applied to lung cancer detection by Jing, Wang, Liew, Siau-Chuin, Azian, Abd Aziz

    Published 2024
    “…The improved multi-scale mean filter approximates the image’s offset field, effectively reducing gray-scale inhomogeneity and eliminating the influence of scale parameter selection on segmentation. …”
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  11. 11
    Automated Region Growing for Segmentation of Brain Lesion in Diffusion-weighted MRI

    Automated Region Growing for Segmentation of Brain Lesion in Diffusion-weighted MRI by Mohd Saad, Norhashimah, Abdullah, Abdul Rahim

    Published 2012
    “…Overall, automated region growing algorithm provides comparable results with the semi-automatic segmentation.…”
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  12. 12
    Computer-aided acute leukemia blast cells segmentation in peripheral blood images

    Computer-aided acute leukemia blast cells segmentation in peripheral blood images by Madhloom, H.T., Kareem, S.A., Ariffin, H.

    Published 2015
    “…The first aim is to segment the leukemic cells by mean of color transformation and mathematical morphology. …”
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  13. 13
    Extremal region selection for MSER detection in food recognition

    Extremal region selection for MSER detection in food recognition by Razali, Mohd Norhisham, Manshor, Noridayu, Abdul Halin, Alfian, Mustapha, Norwati, Yaakob, Razali

    Published 2021
    “…Therefore, this research proposes an Extremal Region Selection (ERS) algorithm to improve MSER detection by reducing the number of irrelevant extremal regions by using unsupervised learning based on the k-means algorithm. …”
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  14. 14
    Spectral texture segmentation of Magnetic Resonance Imaging (MRI) brain images for glioma brain tumour detection / Rosniza Roslan

    Spectral texture segmentation of Magnetic Resonance Imaging (MRI) brain images for glioma brain tumour detection / Rosniza Roslan by Roslan, Rosniza

    Published 2013
    “…Experiments conducted on 64 MRI images, of all sequences showed that texture energy is the best texture feature to be used in glioma segmentation. Fuzzy C-Means clustering algorithm is then used to segment texture energy features from 126 MRI brain images of all sequences. …”
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  15. 15
    Development of lung cancer prediction system using meta-heuristic optimized deep learning model

    Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

    Published 2023
    “…After that cancer-affected region in the lung is segmented with the help of the proposed Butterfly Optimization Algorithm-based K-Means Clustering (BOAKMC) algorithm. …”
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  16. 16
    Extremal Region Selection for MSER Detection in Food Recognition

    Extremal Region Selection for MSER Detection in Food Recognition by Mohd Norhisham Razali @ Ghazali, Noridayu Manshor, Alfian Abdul Halin, Norwati Mustapha, Razali Yaakob

    Published 2021
    “…Therefore, this research proposes an Extremal Region Selection (ERS) algorithm to improve MSER detection by reducing the number of irrelevant extremal regions by using unsupervised learning based on the k-means algorithm. …”
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  17. 17
    A Hybrid K-Means Hierarchical Algorithm for Natural Disaster Mitigation Clustering

    A Hybrid K-Means Hierarchical Algorithm for Natural Disaster Mitigation Clustering by Prasetyadi, Abdurrakhman, Nugroho, Budi, Tohari, Adrin

    Published 2022
    “…Nevertheless, it is difficult to obtain a homogeneous clustering result of the k-means method because this method is sensitive to a random selection of the centers of the cluster. …”
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  18. 18
    Metacarpal phantom radiograph edge detection using genetic algorithm gradient based genotype / Norharyati Md Ariff

    Metacarpal phantom radiograph edge detection using genetic algorithm gradient based genotype / Norharyati Md Ariff by Md Ariff, Norharyati

    Published 2007
    “…For the image segmentation, genetic algorithm are use to segment the bone image and it is a new method that applies in the image processing field. …”
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  19. 19
    A selective approach for energy-aware video content adaptation decision-taking engine in android based smartphone

    A selective approach for energy-aware video content adaptation decision-taking engine in android based smartphone by Ismail, Mohd Norasri

    Published 2019
    “…The EnVADE algorithm uses selective mechanism. Selective mechanism means the video segmented into scenes and adaptation process is done based on the selected scenes. …”
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  20. 20
    A selective approach for energy-aware video content adaptation decision-taking engine in android based smartphone

    A selective approach for energy-aware video content adaptation decision-taking engine in android based smartphone by Abd Rahim, Mohd Hilmi Izwan

    Published 2019
    “…The EnVADE algorithm uses selective mechanism. Selective mechanism means the video segmented into scenes and adaptation process is done based on the selected scenes. …”
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