Search Results - (( java application mining algorithm ) OR ( problem segmentation means algorithm ))
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Direct approach for mining association rules from structured XML data
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Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation
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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Image clustering comparison of two color segmentation techniques
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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A survey: Challenges of image segmentation based fuzzy c-means clustering algorithm
Published 2024journal::journal article -
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Automated Deform Detection On Automotive Body Panels Using Gradient Filtering And Fuzzy C-Mean Segmentation
Published 2016“…It segments the deformation by using Fuzzy C-Means (FCM) segmentation. …”
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Severity Estimation of Plant Leaf Diseases Using Segmentation Method
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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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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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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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…Although effective, these algorithms get stuck in local optima and need proper parameter tuning for solving optimisation problems. …”
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A rule-based image segmentation method and neural network model for classifying fruit in natural environment / Hamirul'aini Hambali
Published 2015“…However, Adaptive K-means has limitation in segmenting black images. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…Although effective, these algorithms get stuck in local optima and need proper parameter tuning for solving optimisation problems. …”
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Computer-aided acute leukemia blast cells segmentation in peripheral blood images
Published 2015“…The first aim is to segment the leukemic cells by mean of color transformation and mathematical morphology. …”
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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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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Final Year Project / Dissertation / Thesis -
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Model-based hybrid variational level set method applied to lung cancer detection
Published 2024“…This enhanced algorithm proves advantageous for addressing real-world image segmentation problems and nodules detection challenges.…”
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AUTOMATED CERVICAL CELL NUCLEI SEGMENTATION BASED ON MULTILAYER UNSUPERVISED CLUSTERING ALGORITHM AND MORPHOLOGICAL APPROACH
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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