You are in the accessibility menu

Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/73741
Full metadata record
DC FieldValueLanguage
dc.contributor.authorOliveira, Roberta B.-
dc.contributor.authorCaldas Jr., Carlos Roberto D.-
dc.contributor.authorPereira, Aledir S.-
dc.contributor.authorGuido, Rodrigo C.-
dc.contributor.authorAraujo, Alex F. de-
dc.contributor.authorTavares, João Manuel R. S.-
dc.contributor.authorRossetti, Ricardo B.-
dc.date.accessioned2014-05-27T11:27:09Z-
dc.date.accessioned2016-10-25T18:39:03Z-
dc.date.available2014-05-27T11:27:09Z-
dc.date.available2016-10-25T18:39:03Z-
dc.date.issued2012-11-19-
dc.identifierhttp://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6263217-
dc.identifier.citationIberian Conference on Information Systems and Technologies, CISTI. Information Systems and Technologies. New York: IEEE, p. 2, 2012.-
dc.identifier.issn2166-0727-
dc.identifier.issn2166-0735-
dc.identifier.urihttp://hdl.handle.net/11449/73741-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/73741-
dc.description.abstractDue to the increased incidence of skin cancer, computational methods based on intelligent approaches have been developed to aid dermatologists in the diagnosis of skin lesions. This paper proposes a method to classify texture in images, since it is an important feature for the successfully identification of skin lesions. For this is defined a feature vector, with the fractal dimension of images through the box-counting method (BCM), which is used with a SVM to classify the texture of the lesions in to non-irregular or irregular. With the proposed solution, we could obtain an accuracy of 72.84%. © 2012 AISTI.en
dc.language.isopor-
dc.sourceScopus-
dc.subjectbox-counting method-
dc.subjectfractal dimension-
dc.subjectintelligent system-
dc.subjectmachine learning-
dc.subjectsupport vector machine-
dc.subjectBox-counting method-
dc.subjectFeature vectors-
dc.subjectSkin cancers-
dc.subjectSkin lesion-
dc.subjectDermatology-
dc.subjectFractal dimension-
dc.subjectImage retrieval-
dc.subjectInformation systems-
dc.subjectIntelligent systems-
dc.subjectLearning systems-
dc.subjectSupport vector machines-
dc.subjectTextures-
dc.subjectImage texture-
dc.titleCharacterization of texture in image of skin lesions by support vector machineen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionUniversidade Do Porto-
dc.description.affiliationDepartamento de Ciências de Computação e Estatísticas Instituto de Biociências, Letras e Ciências Exatas UNESP, São José do Rio Preto-
dc.description.affiliationInstituto de Engenharia Mecânica e Gestão Industrial Faculdade de Engenharia Universidade Do Porto, Porto-
dc.description.affiliationClínica Derm, São José do Rio Preto-
dc.description.affiliationUnespDepartamento de Ciências de Computação e Estatísticas Instituto de Biociências, Letras e Ciências Exatas UNESP, São José do Rio Preto-
dc.identifier.wosWOS:000319285900159-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofIberian Conference on Information Systems and Technologies, CISTI-
dc.identifier.scopus2-s2.0-84869038704-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

There are no files associated with this item.
 

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.