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A population-based ...
A population-based automatic clustering algorithm for image segmentation
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- Mousavirad, Seyed (författare)
- Hakim Sabzevari University, Sabzevar, Iran
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- Schaefer, Gerald (författare)
- Loughborough University, Department of Computer Science, Loughborough, United Kingdom
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- Helali Moghadam, Mahshid (författare)
- Mälardalens högskola,Inbyggda system
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- Saadatmand, Mehrdad, 1980- (författare)
- RISE,Industriella system,Rise Research Institutes of Sweden, Sweden
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- Pedram, Mahdi (författare)
- Lorestan University of Medical Sciences, Iran,Lorestan Univ. of Medical Sciences, Department of Computer Science, Khorramabad, Iran
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(creator_code:org_t)
- 2021-07-08
- 2021
- Engelska.
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Ingår i: GECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion. - New York, NY, USA : Association for Computing Machinery, Inc. - 9781450383516 ; , s. 1931-1936
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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https://urn.kb.se/re...
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Abstract
Ämnesord
Stäng
- Clustering is one of the prominent approaches for image segmentation. Conventional algorithms such as k-means, while extensively used for image segmentation, suffer from problems such as sensitivity to initialisation and getting stuck in local optima. To overcome these, population-based metaheuristic algorithms can be employed. This paper proposes a novel clustering algorithm for image segmentation based on the human mental search (HMS) algorithm, a powerful population-based algorithm to tackle optimisation problems. One of the advantages of our proposed algorithm is that it does not require any information about the number of clusters. To verify the effectiveness of our proposed algorithm, we present a set of experiments based on objective function evaluation and image segmentation criteria to show that our proposed algorithm outperforms existing approaches.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
Nyckelord
- automatic clustering
- human mental search
- image segmentation
- optimisation
- population-based algorithms
- Evolutionary algorithms
- Optimization
- Automatic clustering algorithm
- Conventional algorithms
- K-means
- Local optima
- Meta heuristic algorithm
- Number of clusters
- Optimisation problems
- Population-based algorithm
- K-means clustering
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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