Search Results - (( spatial visualization means algorithm ) OR ( java implication based algorithm ))
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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“…For next, instead of k-means clustring, Fuzzy cmeans clustering is combined with Spatial Pyramid Matching image representation to improve the accuracy of classification results. …”
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Application of terrain analysis to the mapping and spatial pattern analysis of subsurface geological fractures of Kuala Lumpur limestone bedrock, Malaysia.
Published 2012“…Unlike wavelet analysis and the Fourier transform, which use optical remote-sensing images, the integration of visual interpretation and a topographical fabric algorithm is capable of the extraction and spatial correlation of subsurface geological fractures. …”
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Rain streak removal using emboss and spatial-temporal depth filtering technique in video keyframes
Published 2012“…Dynamic weather elements such as rain cause complex visual appearance, because rain consists of spatially distributed drops falling at high velocities. …”
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A hybrid spiking neural network model for multivariate data classification and visualization.
Published 2011“…This study proposes a hybrid model of Self-Organizing Map with modified adaptive coordinates (SOM-AC) and Spiking Neural Network (SNN) for multivariate spatial and temporal data visualization and classification. …”
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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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Video quality assessment method: MD-SSIM
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Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning
Published 2023“…Focusing on clustering algorithms, the study employs popular methods like K-Means Clustering, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Agglomerative Hierarchical Clustering, and Mean Shift Clustering to understand customer characteristics and behaviors. …”
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Moving objects detection from UAV captured videos using trajectories of matched regional adjacency graphs
Published 2017“…The proposed algorithm is designed in order to tackle many limitations of the existing algorithms such as handle inevitable occlusions, model different motions from multiple moving objects, and consider the spatial information.…”
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Rain streaks removal using total variation and sparse coding based on case based reasoning approach
Published 2024journal::journal article -
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Statistical Approach for Image Retrieval
Published 2007“…Of all the visual contents identifiable from an image, colour is considered to be the commonest visual attribute that aids in image retrieval. …”
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Content-based indexing of low resolution documents
Published 2016“…We present hierarchy indexing techniques, whose foundation are tree and clustering. K-means clustering are used for visual features like colour since their spatial distribution give a good image’s global information. …”
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Computed tomography and echocardiography image fusion technique for cardiac images
Published 2016“…For evaluation, beside uncertainty estimation and visually evaluation by experts, quantitative and qualitative evaluations are conducted. …”
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Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh
Published 2020“…Supervised and unsupervised machine learning algorithms particularly the Support Vector Machine (SVM) and Density Based Spatial Clustering of Application with Noise (DBSCAN) are used in this study. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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Numerical and binomial optimal samplings of arthropods of wet paddy ecosystem in Malaysia
Published 1997“…Taylor’s a and b coefficients were then obtained, and incorporated into Wilson and Room’s (1983) algorithms to generate proportions of infestation and OSS information for enumerative and binomial samplings for each arthropod category. …”
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Development of mapping methods for seagrass meadows in Malaysia by using landsat images
Published 2015“…Coastline change was identified as the most significant factor that caused seagrass spatial cover loss of the Pengkalan Nangka lagoon. …”
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Thesis
