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  1. 1
    An improved artificial bee colony algorithm based on mean best-guided approach for continuous optimization problems and real brain MRI images segmentation

    An improved artificial bee colony algorithm based on mean best-guided approach for continuous optimization problems and real brain MRI images segmentation by Alrosan, Ayat, Alomoush, Waleed, Norwawi, Norita, Alswaitti, Mohammed, Makhadmeh, Sharif Naser

    Published 2024
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  2. 2
    Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation

    Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation by Tan , Khang Siang

    Published 2011
    “…Due to its capability in providing a particularly promising solution to clustering problems, the conventional Fuzzy C-Mean (FCM) algorithm is widely used as a segmentation method. …”
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  3. 3
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
    “…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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  4. 4
    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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  5. 5
    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
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  6. 6
    Automated Deform Detection On Automotive Body Panels Using Gradient Filtering And Fuzzy C-Mean Segmentation

    Automated Deform Detection On Automotive Body Panels Using Gradient Filtering And Fuzzy C-Mean Segmentation by Muhammad Zuhair Bolqiah, Edris, Zahriladha, Zakaria, Mohd Shahril Izuan, Mohd Zin, Mohammed Saeed, Jawad

    Published 2016
    “…It segments the deformation by using Fuzzy C-Means (FCM) segmentation. …”
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  7. 7
    Severity Estimation of Plant Leaf Diseases Using Segmentation Method

    Severity Estimation of Plant Leaf Diseases Using Segmentation Method by Chyntia Jaby, Entuni, Tengku Mohd Afendi, Zulcaffle, Kuryati, Kipli, Fatih, Kurugollu

    Published 2020
    “…Combination of Fuzzy C-Means and YCbCr produce 96.81% accuracy. This algorithm is more effective than other algorithms in terms of not only better segmentation performance but also low time complexity that us 34.75s in average with 0.2697s standard deviation.…”
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  8. 8
    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
    “…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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  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 Zuhairi Zamli, Aftab Alam

    Published 2025
    “…Although effective, these algorithms get stuck in local optima and need proper parameter tuning for solving optimisation problems. …”
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  10. 10
    A rule-based image segmentation method and neural network model for classifying fruit in natural environment / Hamirul'aini Hambali

    A rule-based image segmentation method and neural network model for classifying fruit in natural environment / Hamirul'aini Hambali by Hambali, Hamirul'aini

    Published 2015
    “…However, Adaptive K-means has limitation in segmenting black images. …”
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  11. 11
    Feature identification in a real surface metrology analysis by means of Double Iteration Sobel (DIS) / Ainaa Farhanah Mohd Razali

    Feature identification in a real surface metrology analysis by means of Double Iteration Sobel (DIS) / Ainaa Farhanah Mohd Razali by Mohd Razali, Ainaa Farhanah

    Published 2022
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  12. 12
    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
    “…Although effective, these algorithms get stuck in local optima and need proper parameter tuning for solving optimisation problems. …”
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  13. 13
    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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  14. 14
    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
    “…This article introduced a new method based on the combination of genetic algorithm and FCM to solve this problem. The genetic algorithm is used to find initialized centre of the clusters. …”
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  15. 15
    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
    “…This enhanced algorithm proves advantageous for addressing real-world image segmentation problems and nodules detection challenges.…”
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  16. 16
    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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  17. 17
    Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli

    Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli by Ramli, Muhammad Harith

    Published 2017
    “…Bat algorithm is chosen for the development of the prototype for segmentation and classification purpose. …”
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  18. 18
    An Educational Tool Aimed at Learning Metaheuristics

    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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  19. 19
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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  20. 20
    Retinal blood vessel segmentation by using matched filtering and fuzzy C-means clustering with integrated level set method for diabetic retinopathy assessment

    Retinal blood vessel segmentation by using matched filtering and fuzzy C-means clustering with integrated level set method for diabetic retinopathy assessment by Memari, Nogol, Ramli, Abd Rahman, Saripan, M. Iqbal, Mashohor, Syamsiah, Moghbel, Mehrdad

    Published 2019
    “…Methods :In this study, an automatic retinal vessel segmentation utilising fuzzy c-means clustering and level sets is proposed. …”
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