Search Results - (( spatial visualization using algorithm ) OR ( parameter extraction method algorithm ))
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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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Statistical Approach for Image Retrieval
Published 2007“…The system has also included some adjustable parameters, such as window size, CC percentage similarity, which can be used to improve retrieval accuracy. …”
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Development Of Distributed Grid-Based Hydrological Model And Floodplain Inundation Management System
Published 2008“…The land use/cover classes were derived from interpreted information of Landsat TM imagery using the combined object-oriented segmentation - fuzzy logic algorithm. …”
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Parameter extraction of photovoltaic module using hybrid evolutionary algorithm
Published 2023“…Algorithms; Diodes; Extraction; Iterative methods; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Different evolutions; Differential Evolution; Diode modeling; Electromagnetism-like algorithm; Extracting parameter; Hybrid evolutionary algorithm; Photovoltaic model; Photovoltaic modules; Evolutionary algorithms…”
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Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments
Published 2022“…Traditional visual odometry algorithms require the careful fabrication of state-of-the-art building blocks based on geometry. …”
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Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments
Published 2022“…Traditional visual odometry algorithms require the careful fabrication of state-of-the-art building blocks based on geometry. …”
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Compacted dither pattern codes over MPEG-7 dominant colour descriptor in video visual depiction
Published 2010“…Visual description experiments were conducted for ten irregular shapes-based visual concepts in videos with three setups namely CDPC with Bhattacharyya classifier, DCD without spatial coherency and DCD with spatial coherency. …”
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A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model
Published 2023“…Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system…”
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Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm
Published 2023“…Algorithms; Diodes; Errors; Extraction; Iterative methods; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Differential evolution algorithms; Diode modeling; Electromagnetism-like algorithm; Fast convergence speed; Hybrid evolutionary algorithm; IV characteristics; Photovoltaic model; Root mean square errors; Evolutionary algorithms…”
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Novel parameter extraction for single, double, and three diodes photovoltaic models based on robust adaptive arithmetic optimization algorithm and adaptive damping method of Berndt-Hall-Hall-Hausman
Published 2022“…Experimental data-oriented parameter extraction helps in giving an accurate assessment to forecast the output current of the photovoltaic cells. …”
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Pixel value differencing steganography techniques: Analysis and open challenge
Published 2015“…Image steganography is majorly divided into spatial and frequency domains. Pixel value differencing (PVD) considered as good steganographic algorithm due to its high payload and good visual perception in spatial domain. …”
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Extracting crown morphology with a low-cost mobile LiDAR scanning system in the natural environment
Published 2021“…Finally, morphological parameters of the canopy, such as crown height, crown diameter, and crown volume, are extracted using statistical and voxel methods. …”
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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 novel theoretical and practical methodology for extracting the parameters of the single and double diode Photovoltaic models
Published 2022“…However, there is no method to date that can guarantee the extracted parameter of the PV model is the most accurate one. …”
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Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach
Published 2020“…Region merging approach is used to reduce over segmented regions produced by region-based image segmentation algorithms. …”
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17
Development of saliency metric for autonomous landmark selection in cognitive robot navigation / Gao Hanyang
Published 2022“…Urban landmarks are spatial features that are visually significant in the neighbourhood. …”
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Conjunctions in biological neural architectures for visual pose estimation / Tom´As Maul
Published 2006“…The current thesis is concerned with how biological systems solve the computational problem of visual pose estimation. Four levels of analysis are traversed in order of decreasing abstraction: computational, algorithmic, implementational and formational. …”
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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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