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Image Clustering by Generative Adversarial Optimization and Advanced Clustering Criteria
Clustering is the task that has been used in numerous applications including digital image analysis and processing. Image clustering refers to the problem of segmenting image for different purposes which leads to various clustering criteria. Finding the optimal clusters represented by their centers...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7354814/ http://dx.doi.org/10.1007/978-3-030-53956-6_42 |
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author | Tuba, Eva Strumberger, Ivana Bacanin, Nebojsa Bezdan, Timea Tuba, Milan |
author_facet | Tuba, Eva Strumberger, Ivana Bacanin, Nebojsa Bezdan, Timea Tuba, Milan |
author_sort | Tuba, Eva |
collection | PubMed |
description | Clustering is the task that has been used in numerous applications including digital image analysis and processing. Image clustering refers to the problem of segmenting image for different purposes which leads to various clustering criteria. Finding the optimal clusters represented by their centers is a hard optimization problem and it is one of the main research focuses on clustering methods. In this paper we proposed a novel generative adversarial optimization algorithm for finding the optimal cluster centers while using standard and advance clustering criteria. The proposed method was tested on seven benchmark images and results were compared with the artificial bee colony, particle swarm optimization and genetic algorithm. Based on the obtained results, the generative adversarial optimization algorithm founded better cluster centers for image clustering compared to named methods from the literature. |
format | Online Article Text |
id | pubmed-7354814 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-73548142020-07-13 Image Clustering by Generative Adversarial Optimization and Advanced Clustering Criteria Tuba, Eva Strumberger, Ivana Bacanin, Nebojsa Bezdan, Timea Tuba, Milan Advances in Swarm Intelligence Article Clustering is the task that has been used in numerous applications including digital image analysis and processing. Image clustering refers to the problem of segmenting image for different purposes which leads to various clustering criteria. Finding the optimal clusters represented by their centers is a hard optimization problem and it is one of the main research focuses on clustering methods. In this paper we proposed a novel generative adversarial optimization algorithm for finding the optimal cluster centers while using standard and advance clustering criteria. The proposed method was tested on seven benchmark images and results were compared with the artificial bee colony, particle swarm optimization and genetic algorithm. Based on the obtained results, the generative adversarial optimization algorithm founded better cluster centers for image clustering compared to named methods from the literature. 2020-06-22 /pmc/articles/PMC7354814/ http://dx.doi.org/10.1007/978-3-030-53956-6_42 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Tuba, Eva Strumberger, Ivana Bacanin, Nebojsa Bezdan, Timea Tuba, Milan Image Clustering by Generative Adversarial Optimization and Advanced Clustering Criteria |
title | Image Clustering by Generative Adversarial Optimization and Advanced Clustering Criteria |
title_full | Image Clustering by Generative Adversarial Optimization and Advanced Clustering Criteria |
title_fullStr | Image Clustering by Generative Adversarial Optimization and Advanced Clustering Criteria |
title_full_unstemmed | Image Clustering by Generative Adversarial Optimization and Advanced Clustering Criteria |
title_short | Image Clustering by Generative Adversarial Optimization and Advanced Clustering Criteria |
title_sort | image clustering by generative adversarial optimization and advanced clustering criteria |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7354814/ http://dx.doi.org/10.1007/978-3-030-53956-6_42 |
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