A fusion method for multi-valued data
| dc.contributor.author | Papčo, Martin | |
| dc.contributor.author | Rodríguez Martínez, Iosu | |
| dc.contributor.author | Fumanal Idocin, Javier | |
| dc.contributor.author | Altalhi, A. H. | |
| dc.contributor.author | Bustince Sola, Humberto | |
| dc.contributor.department | Estadística, Informática y Matemáticas | es_ES |
| dc.contributor.department | Estatistika, Informatika eta Matematika | eu |
| dc.date.accessioned | 2021-09-14T08:33:11Z | |
| dc.date.available | 2023-07-01T23:00:11Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | In this paper we propose an extension of the notion of deviation-based aggregation function tailored to aggregate multidimensional data. Our objective is both to improve the results obtained by other methods that try to select the best aggregation function for a particular set of data, such as penalty functions, and to reduce the temporal complexity required by such approaches. We discuss how this notion can be defined and present three illustrative examples of the applicability of our new proposal in areas where temporal constraints can be strict, such as image processing, deep learning and decision making, obtaining favourable results in the process. | en |
| dc.description.sponsorship | The research done by Humberto Bustince, Iosu Rodríguez Martínez and Javier Fumanal Idocin has been funded by the project PID2019-108392GB-I00: 3031138640/AEI/10.13039/501100011033. The work of Martin Papčo was supported by the Slovak Research and Development Agency under the contract No. APVV-16-0073. | en |
| dc.embargo.lift | 2023-07-01 | |
| dc.embargo.terms | 2023-07-01 | |
| dc.format.extent | 30 p. | |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.doi | 10.1016/j.inffus.2021.01.001 | |
| dc.identifier.issn | 1566-2535 | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/40483 | |
| dc.language.iso | eng | en |
| dc.publisher | Elsevier | en |
| dc.relation.ispartof | Information Fusion, 71 (2021) 1-10 | en |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-108392GB-I00/ES/ | |
| dc.relation.publisherversion | https://doi.org/10.1016/j.inffus.2021.01.001 | |
| dc.rights | © 2021 Elsevier B.V. This manuscript version is made available under the CC-BY-NC-ND 4.1 | en |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | Aggregation fusion | en |
| dc.subject | Moderate deviation function | en |
| dc.subject | Multi-valued data fusion | en |
| dc.title | A fusion method for multi-valued data | en |
| dc.type | info:eu-repo/semantics/article | |
| dc.type.version | info:eu-repo/semantics/acceptedVersion | |
| dspace.entity.type | Publication | |
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