Search Results - (( problem segmentation search algorithm ) OR ( java adaptation optimization algorithm ))
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Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation
Published 2011“…These algorithms have been applied to the problem of image segmentation. …”
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Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy
Published 2014“…To overcome this problem, two successful swarm-intelligence-based global optimization algorithms, cuckoo search (CS) algorithm and wind driven optimization (WDO) for multilevel thresholding using Kapur’s entropy has been employed. …”
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Vibrant search mechanism for numerical optimization functions
Published 2018“…The proposed method randomly updates the desired segment by monitoring the algorithm search performance levels on different search space divisions. …”
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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Effective predicate identification algorithm for XML retrieval
Published 2018“…Thus, the systems return irrelevant user search intentions. A search intention consists of entity nodes and predicate nodes of XML data. …”
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A survey: Challenges of image segmentation based fuzzy c-means clustering algorithm
Published 2024journal::journal article -
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Data fitting by G1 rational cubic Be´zier curves using harmony search
Published 2015“…A metaheuristic algorithm, called Harmony Search (HS) is implemented for data fitting by rational cubic Be´ zier curves. …”
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Effective query structuring with ranking using named entity categories for XML retrieval
Published 2016“…The systems focus on user query representation, user search intention identification and ranking algorithms to improve keyword search. …”
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Application of shuffled frog leaping algorithm for economic dispatch with multiple fuel options / Muhammad Akif Abu Bakar
Published 2016“…The proposed method in solving economic dispatch problem combines the evolutionary algorithm with analytical approach is capable in performing much better in directing the search towards the optimal region. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…Although effective, these algorithms get stuck in local optima and need proper parameter tuning for solving optimisation problems. …”
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Data Fitting by G1 Rational Cubic Bézier Curves Using Harmony Search
Published 2015“…A metaheuristic algorithm, called Harmony Search (HS) is implemented for data fitting by rational cubic Bézier curves. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…Although effective, these algorithms get stuck in local optima and need proper parameter tuning for solving optimisation problems. …”
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Automated breast profile segmentation for ROI detection using digital mammograms
Published 2023“…Finding an accurate, robust and efficient breast profile segmentation technique still remains a challenging problem in digital mammography. …”
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Computational comparison of major proposed methods for graph partitioning problem
Published 2019“…Local search is one of the earliest methods that has been applied efficiently to this type of problem. …”
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Integrated face detection approach for far image application
Published 2016“…The last stage of the algorithm is to apply the Euler method, in which its function is to search for the facial features. …”
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Online Clothing Shopbots via Web Content Extraction / Nurul Syazwani Ramzi
Published 2017“…By using this algorithm, the web page is segmented into several big blocks. …”
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A method for Arabic handwritten diacritics characters
Published 2019“…Moreover, we introduced a new model based on k-nearest neighbors (KNN) algorithm to identify diacritics and characters segmentation. …”
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A NOVEL FORWARD BACKWARD LINEAR PREDICTION ALGORITHM FOR SHORT TERM POWER LOAD FORECAST
Published 2010“…The proposed AR-based algorithm divides long data record into short segments and searches for the AR coefficients that simultaneously model the data with the least means squared errors. …”
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