Search Results - (( java application optimisation algorithm ) OR ( using segmentation clustering algorithm ))
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Image segmentation based on normalised cuts with clustering algorithm
Published 2013“…Clustered segments from the local segmentation are then used for image segmentation in global perspective. …”
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Thesis -
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Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation
Published 2011“…Fuzzy clustering algorithms, which fall under unsupervised machine learning, are among the most successful methods for image segmentation. …”
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Customer segmentation on clustering algorithms
Published 2023“…This report presents an analysis of customer segmentation using various clustering algorithms, including k-means, DBSCAN, GMM, and RFM. …”
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Final Year Project / Dissertation / Thesis -
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Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor
Published 2010“…This project is about segmentation of FLAIR brain Magnetic Resonance Image (MRI) using K-Means Clustering algorithm. …”
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Performance comparison of clustering and thresholding algorithms for tuberculosis bacilli segmentation.
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Working Paper -
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Enhanced Clustering Algorithms For Gray-Scale Image Segmentation
Published 2012“…The clustering algorithms are widely used as an unsupervised method for image segmentation in medical diagnosis, satellite imaging and biometric systems. …”
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Framework for stream clustering of trajectories based on temporal micro clustering technique
Published 2018“…On the other hand, the offline phase is evoked when the user requests to view the overall clustering results. The DBSCAN algorithm is used to perform the macro clustering task by replacing the distance between trajectories segments with the distance between the temporal micro-clusters. …”
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9
Image clustering comparison of two color segmentation techniques
Published 2010“…There are many algorithm for analysing clustering each having its own method to do clustering. …”
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Improved Fast Fuzzy C-Means Algorithm for Medical MR Images Segmentation
Published 2008“…Fuzzy c-means (FCM) clustering algorithm has been widely used in automated image segmentation. …”
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Article -
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Customer segmentation using clustering techniques / Mohamad Amir Salihin Mustafa
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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Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images
Published 2024Conference Paper -
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Features extraction based on fuzzy clustering and segmentation onto the motion region for medium field surveillance application
Published 2004“…Instead of using blob analysis, we believe that fuzzy based clustering algorithm, can also be used to generate different clusters. …”
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Book Section -
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MRI segmentation of medical images using FCM with initialized class centers via genetic algorithm
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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K-Means Clustering Approach for Intelligent Customer Segmentation Using Customer Purchase Behavior Data
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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Article -
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Cluster approach for auto segmentation of blast in acute leukimia blood slide images
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Working Paper -
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A survey: Challenges of image segmentation based fuzzy c-means clustering algorithm
Published 2024journal::journal article -
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Segmentation of MRI brain images using statistical approaches
Published 2011“…The Gaussian Mixture Model (GMM) is a clustering algorithm that is commonly used for brain MRI segmentation. …”
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Thesis -
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Blood cell image segmentation using unsupervised clustering techniques
Published 2009“…In this paper, we present a framework of comparison cell images segmentation by using unsupervised clustering techniques with the purpose of acquiring the best method to segment the cell images. …”
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