Search Results - (( regional distribution clustering algorithm ) OR ( parameters evaluation a algorithm ))
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A coverage path planning approach for autonomous radiation mapping with a mobile robot
Published 2023Article -
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Model-based hybrid variational level set method applied to object detection in grey scale images
Published 2024“…VKMHLS simplifies the Local Intensity Clustering (LIC) model and introduces a novel energy functional based on the region-based pressure function, enhancing the efficiency of segmentation for low grayscale images. …”
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Scheduled activity energy-aware distributed cluster- based routing algorithm for wireless sensor networks with non-uniform node distribution
Published 2014“…Therefore, in this study, a new algorithm called Scheduled-Activity Energy Aware Distributed Clustering (SA-EADC) is proposed. …”
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Comparison between clustering algorithm for rainfall analysis in Kelantan / Wan Nurshazelin Wan Shahidan and Siti Nurasikin Abdullah
Published 2017“…Comparisons between the clustering algorithms were conducted in this study to identify which clustering algorithm is the most suitable and simple for rainfall distribution. …”
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Clustering of Indonesian forest fires using self organizing maps
Published 2006“…This paper focuses on clustering the locations of Indonesian forest fires and visualizing them into a two-dimensional map using a self-organizing map (SOM) algorithm. …”
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Chemometric approaches in the evaluation of trace metals in commercially raised tilapia and preliminary health risk assessment of its consumption / Low Kah Hin
Published 2012“…The influence of different parameters vary according to the metal element, thus the working conditions for their simultaneous determination were established as a compromise within the optimum region found for each targeted element. …”
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An eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in khyber-pakhtunkhwa, Pakistan
Published 2018“…The EigenSpot algorithm has been recently proposed for detecting space-time disease clusters of arbitrary shapes with no restriction on the distribution and quality of the data, and has shown some promising advantages over the state-of-the-art methods. …”
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An eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in khyber-pakhtunkhwa, Pakistan
Published 2018“…The EigenSpot algorithm has been recently proposed for detecting space-time disease clusters of arbitrary shapes with no restriction on the distribution and quality of the data, and has shown some promising advantages over the state-of-the-art methods. …”
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Enhancing clustering algorithm with initial centroids in tool wear region recognition
Published 2020“…The silhouette value average score is 0.8504 (highest score is 0.9207) of how well-distributed the resulting clusters. The clustering system has identified the tool to stop cutting at approximate VB = 0.213 mm before the tool condition enters the failure region of abnormal phase (VB < 0.250 mm).s The proposed system functioned effectively in clustering the data obtained from cutting tests performed within a reasonable range of wear stages. …”
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Communication and computational cost on parallel algorithm of PDE elliptic type
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Single Earthquake Bond Pricing Framework With Double Trigger Parameters Based On Multi Regional Seismic Information
Published 2024journal::journal article -
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Measurement and QCD analysis of double-differential inclusive jet cross sections in pp collisions at s = 8 $$ \backslashsqrt{s}=8 $$ TeV and cross section ratios to 2.76 and 7 TeV
Published 2017“…Jets are reconstructed using the anti-k T clustering algorithm with a size parameter of 0.7 in a phase space region covering jet p T from 74 GeV up to 2.5 TeV and jet absolute rapidity up to |y| = 3.0. …”
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Using Bimodal Gaussian Mixture Model-Based Algorithm for Background Segmentation in Thermal Fever Mass Screening
Published 2011“…To estimate the bi - modal background-foreground distribution mixture parameters, Expectation-Maximization (EM) algorithm is applied and the images are clustered statistically and linearly. …”
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Visualization of dengue incidences using expectation maximization (EM) algorithm
Published 2017“…Along with the prediction modeling on data using centroid model and distribution model based on K-means and Expectation Maximization (EM) algorithms respectively. …”
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Development of lung cancer prediction system using meta-heuristic optimized deep learning model
Published 2023“…After that cancer-affected region in the lung is segmented with the help of the proposed Butterfly Optimization Algorithm-based K-Means Clustering (BOAKMC) algorithm. …”
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A hybrid method using haar-like and skin-color algorithm for hand posture detection, recognition and tracking
Published 2010“…The chromatic color distribution of skin can be found within this cluster. …”
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Haemoglobin distribution in ulcers for healing assessment
Published 2012“…Extracted haemoglobin images indicate areas of haemoglobin distribution reflecting detected regions of granulation tissue. …”
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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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Species distribution and molecular variations in drogonflies (order: odonata) within the state of Selangor, Malaysia / Noorhidayah Binti Mamat
Published 2013“…Opposite to suborder Zygoptera, they were resolved clustered into 2 clusters, paraphyletic group. The distinct separation between cluster Anisoptera and Zygoptera with confidence level 72% in the NJ analyses while 90% in MP analyses. …”
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