Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/54196
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dc.contributor.authorSuárez Araujo, Carmen Pazen_US
dc.date.accessioned2019-02-18T09:14:26Z-
dc.date.available2019-02-18T09:14:26Z-
dc.date.issued1997en_US
dc.identifier.issn0924-9907en_US
dc.identifier.urihttp://hdl.handle.net/10553/54196-
dc.description.abstractIn this paper we propose a theoretical approach toinvariant perception. Invariant perception is an importantaspect in both natural and artificial perception systems, and itremains an important unsolved problem in heuristically basedpattern recognition. Our approach is based on a general theoryof neural networks and studies of invariant perception by thecortex. The neural structures that we propose uphold both thearchitecture and functionality of the cortex as currentlyunderstood. The formulation of the proposed neural structuresis in the language of image algebra, a mathematical environmentfor expressing image processing algorithms. Thus, an additionalbenefit of our study is the implication that image algebraprovides an excellent environment for expressing and developingartificial perception systems. The focus of our study is oninvariances that are expressible in terms of affinetransformations, specifically, homothetic transformations. Ourdiscussion will include both one-dimensional andtwo-dimensional signal patterns. The main contribution of thispaper is the formulation of several novel morphological neuralnetworks that compute homothetic auditory and visualinvariances. With respect to the latter, we employ the theoryand trends of currently popular artificial vision systems.en_US
dc.languageengen_US
dc.publisher0924-9907-
dc.relation.ispartofJournal of Mathematical Imaging and Visionen_US
dc.sourceJournal of Mathematical Imaging and Vision [ISSN 0924-9907], v. 7, p. 69-83en_US
dc.subject120304 Inteligencia artificialen_US
dc.subject.otherMorphological neural networksen_US
dc.subject.otherimage algebraen_US
dc.subject.otherInvariant perceptionen_US
dc.subject.otherHomothetical invariances perceptionen_US
dc.titleNovel neural network models for computing homothetic invariances: an image algebra notationen_US
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.typeArticleen_US
dc.identifier.doi10.1023/A:1008218108171en_US
dc.identifier.scopus0030786147-
dc.identifier.isiA1997WJ08300006-
dc.contributor.authorscopusid6603605708-
dc.description.lastpage83en_US
dc.description.firstpage69en_US
dc.relation.volume7en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Artículoen_US
dc.contributor.daisngid1776211-
dc.utils.revisionen_US
dc.contributor.wosstandardWOS:Araujo, CPS-
dc.date.coverdateDiciembre 1997en_US
dc.identifier.ulpgcen_US
dc.description.scieSCIE
item.fulltextSin texto completo-
item.grantfulltextnone-
crisitem.author.deptGIR IUCES: Computación inteligente, percepción y big data-
crisitem.author.deptIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.orcid0000-0002-8826-0899-
crisitem.author.parentorgIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.fullNameSuárez Araujo, Carmen Paz-
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