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  1. 1
    An improved fast scanning algorithm based on distance measure and threshold function in region image segmentation

    An improved fast scanning algorithm based on distance measure and threshold function in region image segmentation by Ismael, Ahmed Naser

    Published 2016
    “…Various algorithms have been proposed for image segmentation and this includes the Fast Scanning algorithm which has been employed on food, sport and medical image segmentation. …”
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  2. 2
    Development Of Automatic Liver Segmentation Method For Three- Dimensional Computed Tomography Dataset

    Development Of Automatic Liver Segmentation Method For Three- Dimensional Computed Tomography Dataset by Chew, Chin Boon

    Published 2018
    “…Therefore, an automated liver segmentation algorithm is proposed and developed in this project to improve the accuracy and time required for liver segmentation. …”
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  3. 3
    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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  4. 4
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…The simulation is implemented with iFogSim and java programming language. …”
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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
    “…These algorithms have been applied to the problem of image segmentation. …”
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  6. 6
    Brain tumor image segmentation using deep learning approach

    Brain tumor image segmentation using deep learning approach by Darshan, Suresh

    Published 2022
    “…In addition, the existing software for brain tumor segmentation are implemented using conventional image segmentation algorithms which are labor intensive and causes over or under segmented tumor regions. …”
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  7. 7
    Segmentation of Lung Region in Computed Tomography (CT) Images

    Segmentation of Lung Region in Computed Tomography (CT) Images by Mohd Bokeri, Husna Adila

    Published 2015
    “…In this work, a lung segmentation algorithm for CT images is proposed and evaluated. …”
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    Final Year Project
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  8. 8
    Image enhancement and segmentation on simultaneous latent fingerprint detection

    Image enhancement and segmentation on simultaneous latent fingerprint detection by Rozita, Mohd Yusof

    Published 2015
    “…The results show that the proposed algorithm achieves a correct segmentation of 77.5% of the SLF images under test.…”
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  9. 9
    Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images

    Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

    Published 2024
    “…This proposed algorithm achieved segmentation accuracy of 96.8% and 92.1% for ISIC and PH2 datasets respectively. …”
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  10. 10
    Temporal video segmentation using squared form of Krawtchouk-Tchebichef moments

    Temporal video segmentation using squared form of Krawtchouk-Tchebichef moments by Abdulhussain, Sadiq H.

    Published 2018
    “…The performance of the proposed algorithm is compared to that of several state-of-the-art TVS algorithms. …”
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  11. 11
    An Automated Image Segmentation and Useful Feature Extraction Algorithm for Retinal Blood Vessels in Fundus Images

    An Automated Image Segmentation and Useful Feature Extraction Algorithm for Retinal Blood Vessels in Fundus Images by Abdulsahib A.A., Mahmoud M.A., Aris H., Gunasekaran S.S., Mohammed M.A.

    Published 2023
    “…The main pipeline of the proposed algorithm is composed of two essential stages: image segmentation and clinical features extraction stage. …”
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  12. 12
    Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation

    Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation by Rahimizadeh, Hamid

    Published 2009
    “…Experimental results show that the proposed algorithm works better than other two methods in terms of classifier accuracy with result of more than 99 percent successful segmentation of desired color in varying illumination. …”
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  13. 13
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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  14. 14
    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
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  15. 15
    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
    “…For liver vasculature segmentation, a mean overlap error of 35.9% and mean absolute relative volume difference of 16.7% was achieved by using the proposed segmentation method, making it amongst the most accurate liver vasculature segmentation methods. …”
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  16. 16
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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  17. 17
    Novel techniques for enhancement and segmentation of acne vulgaris lesions

    Novel techniques for enhancement and segmentation of acne vulgaris lesions by Malik, A. S., Humayun, J., Kamel, N., Yap, F. B.-B.

    Published 2013
    “…The proposed algorithm uses local rank transform to generate the HDR images from a single acne image followed by the log transformation. …”
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    Citation Index Journal
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  18. 18
    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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  19. 19
    UNSUPERVISED SEGMENTATION OF CORAL REEF IMAGES BY USING COLOR AND TEXTURE FEATURES

    UNSUPERVISED SEGMENTATION OF CORAL REEF IMAGES BY USING COLOR AND TEXTURE FEATURES by MOHAMMAD SAMEER ALOUN

    Published 2022
    “…The unsupervised segmentation of color-texture regions using J-value segmentation (JSEG) algorithm is one of the most popular and robust unsupervised segmentation algorithms. …”
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  20. 20
    Image storage and retrieval using color quantization method

    Image storage and retrieval using color quantization method by Mandal, Koushik Kanti, Islam, Md. Rafiqul, Md. Sap, Mohd. Noor, Khatun, Fahmida, Reza, Md. Parvez

    Published 2005
    “…The image is segmented by our proposed segmentation algorithm, which uses the compact color descriptor .The result of the experiment shows that the developed segmentation algorithm produces better performances as compared with the existing segmentation algorithm. …”
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