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  1. 1
    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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  2. 2
    Image clustering comparison of two color segmentation techniques

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

    Published 2010
    “…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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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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    Final Year Project / Dissertation / Thesis
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  4. 4
    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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  5. 5
    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
    “…However, two main issues plague these clustering algorithms: initialization sensitivity of cluster centers and unknown number of actual clusters in the given dataset. …”
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  6. 6
    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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  7. 7
    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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  8. 8
    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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    Conference or Workshop Item
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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
    Survey on Clustered Routing Protocols Adaptivity for Fire Incidents: Architecture Challenges, Data Losing, and Recommended Solutions

    Survey on Clustered Routing Protocols Adaptivity for Fire Incidents: Architecture Challenges, Data Losing, and Recommended Solutions by Abbas O.K., Abdullah F., Radzi N.A.M., Salman A.D., Abdulkadir S.J.

    Published 2025
    “…Cluster Heads (CHs), selected through a range of metrics, are responsible for data aggregation and transmission to the Base Station (BS). …”
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  11. 11
    CC_TRS: continuous clustering of trajectory stream data based on micro cluster life

    CC_TRS: continuous clustering of trajectory stream data based on micro cluster life by Abdulrazzaq, Musaab Riyadh, Mustapha, Norwati, Sulaiman, Md. Nasir, Mohd Sharef, Nurfadhlina

    Published 2017
    “…In this article, an algorithm for Continuous Clustering of Trajectory Stream Data Based on Micro Cluster Life is proposed. …”
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  12. 12
    Individual-tree segmentation and extraction based on LiDAR point cloud data

    Individual-tree segmentation and extraction based on LiDAR point cloud data by Liu, Xiaofeng, Abdullah, Muhamad Taufik, Mustaffa, Mas Rina, Nasharuddin, Nurul Amelina

    Published 2024
    “…Utilizing LiDAR point cloud data and ground-measured data from 30 plots, we examined the sensitivity of individual tree segmentation to key parameters by varying the grid values of the point cloud distance discriminant clustering algorithm and adjusting the canopy height resolution (CHR) of the watershed algorithm. …”
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  13. 13
    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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  14. 14
    Customer mobile behavioral segmentation and analysis in telecom using machine learning

    Customer mobile behavioral segmentation and analysis in telecom using machine learning by Sharaf Addin, Eman Hussein, Admodisastro, Novia Indriaty, Mohd Ashri, Siti Nur Syahirah, Kamaruddin, Azrina, Chew, Yew Chong

    Published 2021
    “…The study applied analytic pipeline that involved five stages i.e. data generation, data pre-processing, data clustering, clusters analysis, and data visualization. …”
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  15. 15
    Customer profiling using K-means clustering method / Nik Asyraniasna Nik Mohd Asri

    Customer profiling using K-means clustering method / Nik Asyraniasna Nik Mohd Asri by Nik Mohd Asri, Nik Asyraniasna

    Published 2024
    “…Through the analysis of various customer data sets, such as people, products, promotion, place, the K-means algorithm can detect clusters that correspond to consistent client groups. …”
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  16. 16
    A Center-Based Stable Evolving Clustering Algorithm With Grid Partitioning And Extended Mobility Features For VANETs

    A Center-Based Stable Evolving Clustering Algorithm With Grid Partitioning And Extended Mobility Features For VANETs by Talib, Mohammed Saad, Abdullah, Nihad Ibrahim, Hassan, Aslinda, Abal Abas, Zuraida, Mohammed Al-Khazraji, Ali Abdul-Jabbar, Alamery, Thamer, Ibrahim, Ali Jalil

    Published 2020
    “…An improvement percentage of the efficiency in (CEC-GP) over the benchmarks Center based stable clustering (CBSC) and evolving data clustering algorithm (EDCA) is 65% and 394% respectively.…”
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  17. 17
    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
    “…Methodology of this research consists of Planning and Analysis, Data Collection, Algorithm Design and Development and Testing. …”
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  18. 18
    Data stream clustering by divide and conquer approach based on vector model

    Data stream clustering by divide and conquer approach based on vector model by Khalilian, Madjid, Mustapha, Norwati, Sulaiman, Nasir

    Published 2016
    “…The continuous effort on data stream clustering method has one common goal which is to achieve an accurate clustering algorithm. …”
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  19. 19
    A new hybrid technique for nosologic segmentation of primary brain tumors / Shafaf Ibrahim

    A new hybrid technique for nosologic segmentation of primary brain tumors / Shafaf Ibrahim by Ibrahim, Shafaf

    Published 2015
    “…On the other hand, the ANFIS is found to have limited pixel detection in nosologic segmentation of primary brain tumors. The CAPSOCA was proven to be the best algorithm for nosologic segmentation of primary brain tumors from the MRI images data. …”
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  20. 20
    Multi-Hop Selective Constructive Interference Flooding Protocol For Wireless Sensor Networks

    Multi-Hop Selective Constructive Interference Flooding Protocol For Wireless Sensor Networks by Alhalabi, Huda A. H.

    Published 2019
    “…MSCIF integrates three main algorithms: clustering algorithm, selection algorithm, and a synchronized flooding. …”
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