Automatic segmentation of the secondary austenite-phase island precipitates in a superduplex stainless steel weld metal

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniv Fortaleza-
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.contributorUniv Fed Ceara-
Autor(es): dc.contributorUniv Porto-
Autor(es): dc.creatorAlbuquerque, Victor H. C.-
Autor(es): dc.creatorNakamura, Rodrigo Y. M. [UNESP]-
Autor(es): dc.creatorPapa, Joao P. [UNESP]-
Autor(es): dc.creatorSilva, Cleiton C.-
Autor(es): dc.creatorTavares, Joao Manuel R. S.-
Autor(es): dc.creatorTavares, JMRS-
Autor(es): dc.creatorJorge, RMN-
Data de aceite: dc.date.accessioned2022-02-22T00:08:27Z-
Data de disponibilização: dc.date.available2022-02-22T00:08:27Z-
Data de envio: dc.date.issued2020-12-09-
Data de envio: dc.date.issued2020-12-09-
Data de envio: dc.date.issued2012-01-01-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/196095-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/196095-
Descrição: dc.descriptionDuplex and superduplex stainless steels are class of materials of a high importance for engineering purposes, since they have good mechanical properties combination and also are very resistant to corrosion. It is known as well that the chemical composition of such steels is very important to maintain some desired properties. In the past years, some works have reported that. 2 precipitation improves the toughness of such steels, and its quantification may reveals some important information about steel quality. Thus, we propose in this work the automatic segmentation of. 2 precipitation using two pattern recognition techniques: Optimum-Path Forest (OPF) and a Bayesian classifier. To the best of our knowledge, this if the first time that machine learning techniques are applied into this area. The experimental results showed that both techniques achieved similar and good recognition rates.-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
Descrição: dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
Descrição: dc.descriptionCearense Foundation for the Support of Scientific and Technological Development (FUNCAP)-
Descrição: dc.descriptionUNIFOR-
Descrição: dc.descriptionUniv Fortaleza, Ctr Ciencias Tecnol, Fortaleza, Ceara, Brazil-
Descrição: dc.descriptionUniv Estadual Paulista, UNESP, Dept Comp, Bauru, Brazil-
Descrição: dc.descriptionUniv Fed Ceara, Dept Engn Met & Mat, Fortaleza, Ceara, Brazil-
Descrição: dc.descriptionUniv Porto, Fac Engn, Oporto, Portugal-
Descrição: dc.descriptionUniv Estadual Paulista, UNESP, Dept Comp, Bauru, Brazil-
Descrição: dc.descriptionFAPESP: 2009/16206-1-
Formato: dc.format161-166-
Idioma: dc.languageen-
Publicador: dc.publisherCrc Press-taylor & Francis Group-
Relação: dc.relationComputational Vision And Medical Image Processing: Vipimage 2011-
???dc.source???: dc.sourceWeb of Science-
Título: dc.titleAutomatic segmentation of the secondary austenite-phase island precipitates in a superduplex stainless steel weld metal-
Aparece nas coleções:Repositório Institucional - Unesp

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