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Efficient image retrieval by fuzzy rules from boosting and metaheuristic

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dc.title Efficient image retrieval by fuzzy rules from boosting and metaheuristic en
dc.contributor.author Korytkowski, Marcin
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Scherer, Magdalena M.
dc.contributor.author Angryk, Rafal A.
dc.contributor.author Kordos, Miroslaw
dc.contributor.author Siwocha, Agnieszka
dc.relation.ispartof Journal of Artificial Intelligence and Soft Computing Research
dc.identifier.issn 2449-6499 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.issn 2083-2567 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2020
utb.relation.volume 10
utb.relation.issue 1
dc.citation.spage 57
dc.citation.epage 69
dc.type article
dc.language.iso en
dc.publisher Sciendo
dc.identifier.doi 10.2478/jaiscr-2020-0005
dc.relation.uri https://content.sciendo.com/configurable/contentpage/journals$002fjaiscr$002f10$002f1$002farticle-p57.xml
dc.subject image retrieval en
dc.subject fuzzy rules en
dc.subject local image features en
dc.description.abstract Fast content-based image retrieval is still a challenge for computer systems. We present a novel method aimed at classifying images by fuzzy rules and local image features. The fuzzy rule base is generated in the first stage by a boosting procedure. Boosting meta-learning is used to find the most representative local features. We briefly explore the utilization of metaheuristic algorithms for the various tasks of fuzzy systems optimization. We also provide a comprehensive description of the current best-performing DISH algorithm, which represents a powerful version of the differential evolution algorithm with effective embedded mechanisms for stronger exploration and preservation of the population diversity, designed for higher dimensional and complex optimization tasks. The algorithm is used to fine-tune the fuzzy rule base. The fuzzy rules can also be used to create a database index to retrieve images similar to the query image fast. The proposed approach is tested on a state-of-the-art image dataset and compared with the bag-of-features image representation model combined with the Support Vector Machine classification. The novel method gives a better classification accuracy, and the time of the training and testing process is significantly shorter. © 2020 Marcin Korytkowski et al., published by Sciendo. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1009514
utb.identifier.obdid 43881275
utb.identifier.scopus 2-s2.0-85077117526
utb.identifier.wok 000502574500005
utb.source j-scopus
dc.date.accessioned 2020-01-09T10:31:41Z
dc.date.available 2020-01-09T10:31:41Z
dc.description.sponsorship program of the Polish Minister of Science and Higher Education under the name "Regional Initiative of Excellence" in the years 2019-2022 [020/RID/2018/19]
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.access openAccess
utb.contributor.internalauthor Šenkeřík, Roman
utb.fulltext.affiliation Marcin Korytkowski 1∗, Roman Senkerik 2, Magdalena M. Scherer 3, Rafal A. Angryk 4, Miroslaw Kordos 5, Agnieszka Siwocha 6 1 Department of Computer Engineering, Czestochowa University of Technology, Czestochowa, Poland 2 Tomas Bata University in Zlín, 760 05 Zlín, Czech Republic 3 Faculty of Management, Czestochowa University of Technology, Czestochowa, Poland 4 Department of Computer Science, Georgia State University, Atlanta, GA, USA 5 Department of Computer Science and Automatics, University of Bielsko-Biała, Poland 6 Information Technology Institute, University of Social Science, Łodz, Poland Clark University, Worcester, MA 01610, USA ∗ E-mail: marcin.korytkowski@pcz.pl
utb.fulltext.dates Submitted: 14th September 2019 Accepted: 16th November 2019
utb.fulltext.sponsorship This work was supported by the project financed under the program of the Polish Minister of Science and Higher Education under the name "Regional Initiative of Excellence" in the years 2019- 2022 project number 020/RID/2018/19, the amount of financing 12,000,000.00 PLN.
utb.wos.affiliation [Korytkowski, Marcin] Czestochowa Tech Univ, Dept Comp Engn, Czestochowa, Poland; [Senkerik, Roman] Tomas Bata Univ Zlin, Zlin 76005, Czech Republic; [Scherer, Magdalena M.] Czestochowa Tech Univ, Fac Management, Czestochowa, Poland; [Angryk, Rafal A.] Georgia State Univ, Dept Comp Sci, Atlanta, GA 30303 USA; [Kordos, Miroslaw] Univ Bielsko Biala, Dept Comp Sci & Automat, Bielsko Biala, Poland; [Siwocha, Agnieszka] Univ Social Sci, Informat Technol Inst, Lodz, Poland; [Siwocha, Agnieszka] Clark Univ, Worcester, MA 01610 USA
utb.scopus.affiliation Department of Computer Engineering, Czȩstochowa University of Technology, Czȩstochowa, Poland; Tomas Bata University in Zlín, Zlín, 760 05, Czech Republic; Faculty of Management, Czȩstochowa University of Technology, Czȩstochowa, Poland; Department of Computer Science, Georgia State University, Atlanta, GA, United States; Department of Computer Science and Automatics, University of Bielsko, Biała, Poland; Information Technology Institute, University of Social Science, Łódź, Poland; Clark University, Worcester, MA 01610, United States
utb.fulltext.projects 020/RID/2018/19
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