Aggregation functions based on the Choquet integral applied to image resizing
| dc.contributor.author | Bueno, Jéssica C. S. | |
| dc.contributor.author | Dias, Camila A. | |
| dc.contributor.author | Pereira Dimuro, Graçaliz | |
| dc.contributor.author | Santos, Helida | |
| dc.contributor.author | Bustince Sola, Humberto | |
| dc.contributor.department | Estatistika, Informatika eta Matematika | eu |
| dc.contributor.department | Institute of Smart Cities - ISC | en |
| dc.contributor.department | Estadística, Informática y Matemáticas | es_ES |
| dc.date.accessioned | 2021-03-05T11:32:50Z | |
| dc.date.available | 2021-03-05T11:32:50Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | The rising volume of data and its high complexity has brought the need of developing increasingly efficient knowledge extraction techniques, which demands efficiency both in computational cost and in accuracy. Most of problems that are handled by these techniques has complex information to be identified. So, machine learning methods are frequently used, where a variety of functions can be applied in the different steps that are employed in their architecture. One of them is the use of aggregation functions aiming at resizing images. In this context, we introduce a study of aggregation functions based on the Choquet integral, whose main characteristic in comparison with other aggregation functions is that it considers, through fuzzy measure, the interaction between the elements to be aggregated. Thus, our main goal is to present an evaluation study of the performance of the standard Choquet integral the and copula-based generalization of the Choquet integral in relation to the maximum and mean functions, looking for results that may be better than the aggregation functions commonly applied. The results of such comparisons are promising, when evaluated through image quality metrics. | en |
| dc.description.sponsorship | The authors Camila Dias and Jessica Bueno thank CAPES for the financial support received. Gracaliz P. Dimuro has funding from CNPq/Brazil (process number 305882/20163). Eduardo N. Borges has funding from FAPERGS (TO 17/2551-0000872-3). Humberto Bustince is supported by the Spanish Ministry of Science and Technology (under project TIN2016-77356-P (AEI/FEDER, UE)). | en |
| dc.format.extent | 7 p. | |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.isbn | 978-94-6252-770-6 | |
| dc.identifier.issn | 2589-6644 | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/39349 | |
| dc.language.iso | eng | en |
| dc.publisher | Atlantis Press | en |
| dc.relation.ispartof | Proceedings of the 11th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2019), Vol. 1, pp. 460-466 | en |
| dc.relation.projectID | info:eu-repo/grantAgreement/ES/1PE/TIN2016-77356-P/ | |
| dc.rights | © 2019, the Authors. This is an open access article under the CC BY-NC license. | en |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0/ | |
| dc.subject | Choquet integral | en |
| dc.subject | Aggregation functions | en |
| dc.subject | Image processing | en |
| dc.title | Aggregation functions based on the Choquet integral applied to image resizing | en |
| dc.type | info:eu-repo/semantics/conferenceObject | |
| dc.type.version | info:eu-repo/semantics/publishedVersion | |
| dspace.entity.type | Publication | |
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