Search Results - (( developing visualization clustering algorithm ) OR ( java application mmla algorithm ))
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In cluster labelling process, a cluster labelling algorithm based on calculation of minimum-distance (MD) between cluster mean and class mean was developed to label the clusters. …”
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Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization
Published 2024thesis::doctoral thesis -
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Fuzzy Soft Set Clustering for Categorical Data
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Clustering autism spectrum disorder student’s system based on intelligence, skills and behavior using agglomerative clustering algortihm / Daarin Nadia Nordin
Published 2020“…Data cleaning and data transformation is first carried out, followed by normalization through the Z-score method before being processed in the clustering model. Several charts such as dendrograms and sunburst charts are used to visualize the clustering results. …”
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Customer mobile behavioral segmentation and analysis in telecom using machine learning
Published 2021“…Lastly, a dashboard was developed using Microsoft Power BI to visualize the clustering results in meaningful analysis. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…Each web services are easily maintainable since there is loose coupling between interacting nodes. The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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Visualization of dengue incidences using expectation maximization (EM) algorithm
Published 2017“…R-GIS(R software) and clustering algorithm were used for year 2014 with several weeks to develop the relation between the visualization and prediction of reported incidences. …”
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Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning
Published 2023“…The findings underscore the pivotal role of AI in navigating and unraveling customer behavior complexities in the banking industry. All clustering models are developed successfully in producing cluster results. …”
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K-means Clustering Analysis for EEG Features of Situational Interest Detection in Classroom Learning
Published 2021“…The mean power for each sub-frequency band was served as input to the k-means algorithm. Results showed that EEG features can be successfully clustered in the alpha frequency band at the frontal region when visual-auditory stimuli are introduced to the subjects. …”
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Pseudo-colour with K-means Clustering Algorithm for Acute Ischemic Stroke Lesion Segmentation in Brain MRI
Published 2021“…The greyscale image is converted to pseudo-colour is to intensify the visual perception and deliver more information. Then, the algorithm segments the region of interest (ROI) using K-means clustering. …”
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3D surface roughness measurement for scaliness scoring of psoriasis lesions
Published 2013“…The reliability of the developed PASI scaliness algorithm was high with kappa coefficients>0.84 (almost perfect agreement). …”
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Unsupervised place recognition for assistive mobile robots based on local feature descriptions.
Published 2011“…In this paper, a robust appearance-based unsupervised place clustering and recognition algorithm is introduced. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…Beside that, classic bag of visual words algorithm (BoVW) is based on kmeans clustering and every SIFT feature belongs to one cluster and it leads to decreasing classification results. …”
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Unsupervised and online place recognition for mobile robot based on local features description
Published 2013“…In this paper, a robust appearance-based unsupervised and online place recognition algorithm, which is inspired from online sequential clustering methods, is introduced. …”
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Unsupervised classification of multi-class chart images: A comparison of customized CNNs and transfer learning techniques
Published 2025“…The k-means clustering algorithm is then applied to group visually similar chart images. …”
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Quantitative Analysis And Mapping Of Concrete Scanning Electron Microscope (SEM) Images
Published 2018“…By spatial segmentation of K-Means algorithms, the cluster groups generated were carefully reviewed before proceeding to the final analysis. …”
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Tumor Extraction for Brain Magnetic Resonance Imaging Using Modified Gaussian Distribution
Published 2006“…The mutual information algorithms used in this work has been developed and experimented in the system and has proven to yield more accurate and stable results than other algorithms. …”
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STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION
Published 2021“…A profound algorithm comprising of preprocessing in CIELAB color space and Delaunay triangulation based clustering along with Particle Swarm Optimization (PSO) is proposed for the segmentation. …”
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