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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.<\/jats:p>","DOI":"10.2478\/jaiscr-2020-0005","type":"journal-article","created":{"date-parts":[[2019,12,12]],"date-time":"2019-12-12T04:32:41Z","timestamp":1576125161000},"page":"57-69","source":"Crossref","is-referenced-by-count":28,"title":["Efficient Image Retrieval by Fuzzy Rules from Boosting and Metaheuristic"],"prefix":"10.2478","volume":"10","author":[{"given":"Marcin","family":"Korytkowski","sequence":"first","affiliation":[{"name":"Department of Computer Engineering , Cz\u0119stochowa University of Technology , Cz\u0119stochowa , Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roman","family":"Senkerik","sequence":"additional","affiliation":[{"name":"Tomas Bata University in Zl\u00edn , 760 05 Zl\u00edn , Czech Republic"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Magdalena M.","family":"Scherer","sequence":"additional","affiliation":[{"name":"Faculty of Management , Cz\u0119stochowa University of Technology , Cz\u0119stochowa , Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rafal A.","family":"Angryk","sequence":"additional","affiliation":[{"name":"Department of Computer Science , Georgia State University , Atlanta , GA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miroslaw","family":"Kordos","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Automatics , University of Bielsko-Bia\u0142a , Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Agnieszka","family":"Siwocha","sequence":"additional","affiliation":[{"name":"Information Technology Institute , University of Social Science, \u0141\u00f3d\u017a , Poland ; Clark University , Worcester , MA 01610 , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2019,12,11]]},"reference":[{"key":"2026042812101181345_j_jaiscr-2020-0005_ref_001_w2aab3b7b5b1b6b1ab1ab1Aa","doi-asserted-by":"crossref","unstructured":"[1] Alharbi, A., Tchier, F.: Using a genetic-fuzzy algorithm as a computer aided diagnosis tool on saudi arabian breast cancer database. 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