Search Results - (( frames detection method algorithm ) OR ( parallel distribution clustering algorithm ))*
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Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim
Published 2012“…This project focuses on step-up cluster computing and a parallel Genetic Algorithm. …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
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MOSIX: Implementation, trend and benchmark in Malaysia
Published 2023Subjects: “…Clustering…”
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The AGEB algorithm for solving the heat equation in two space dimensions and its parallelization on a distributed memory machine
Published 2023Subjects:Article -
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Communication and computational cost on parallel algorithm of PDE elliptic type
Published 2009“…The parallel algorithms of 2-dimensional Partial Differential Equation (PDE) elliptic type for the prediction will be executed using distributed memory of heterogeneous cluster platform on LINUX-based environment. …”
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On An Improved Parallel Construction Of Suffix Arrays For Low Bandwidth Pc-Cluster.
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The visualization of three dimensional brain tumors' growth on distributed parallel computer systems
Published 2009“…The main objective of this study is to visualize the brain tumors’ growth in three-dimensional and implement the algorithm on distributed parallel computer systems. …”
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Depth frame loss concealment for wireless transmission utilising motion detection information
Published 2014“…The methods are able to facilitate a frame copy algorithm and a high correlation of colour and depth frames to conceal depth frame loss. …”
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Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes
Published 2007“…Genetic Algorithm as one of the Evolutionary Computation method improve the execution of parallel programming codes by optimizing the number of processors and the distribution of data. …”
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A New Approach of Optimal Search Solution in Particle Swarm Optimization (PSO) Algorithm for Object Detection Method
Published 2018“…Therefore, to overcome the several problems associated with the object detection method, a new approach in Particle Swarm Optimization (PSO) algorithm for optimal search solution as an alternative method to detect of object tracking quickly, precisely and accurately. …”
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Automated threshold detection for object segmentation in colour image
Published 2016“…In solving this issue, this paper presents an Automated Threshold Detection Algorithm, H(•). The algorithm is applied in segmenting human lower limbs from a series of image frames of human walking. …”
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Ulcer detection and classification of wireless capsule endoscopy images using RGB masking
Published 2016“…This algorithm of capsule images can be clinically very useful as it can discriminate between normal and abnormal frame. …”
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Ulcer detection and classification of wireless capsule endoscopy images using RGB masking
Published 2016“…This algorithm of capsule images can be clinically very useful as it can discriminate between normal and abnormal frame. …”
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Quantification and segmentation of breast cancer diagnosis: efficient hardware accelerator approach
Published 2022“…In addition, a new image clustering algorithm anticipates the need for largescale serial and parallel processing. …”
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An Improved Action Key Frames Extraction Algorithm for Complex Colour Video Shot Summarization
Published 2019“…The objective of this work is to improve our previous action key frames extraction algorithm (AKF) by adapting a threshold which selects action key frames as final key frames. …”
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Implementation of Parallel K-Means Algorithm to Estimate Adhesion Failure in Warm Mix Asphalt
Published 2020“…The results showed that the PKIP algorithm decreases the execution time up to 30 to 46 if compared with the sequential k means algorithm when implemented using multiprocessing and distributed computing. …”
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