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Publicação:
Pattern Recognition in Thermal Images of Plants Pine Using Artificial Neural Networks

dc.contributor.authorColturato, Adimara Bentivoglio
dc.contributor.authorGomes, Andre Benjamin
dc.contributor.authorPigatto, Daniel Fernando
dc.contributor.authorColturato, Danielle Bentivoglio
dc.contributor.authorRoschildt Pinto, Alex Sandro [UNESP]
dc.contributor.authorCastelo Branco, Luiz Henrique
dc.contributor.authorFurtado, Edson Luiz [UNESP]
dc.contributor.authorJaquie Castelo Branco, Kalinka Regina Lucas
dc.contributor.authorIliadis, L.
dc.contributor.authorPapadopoulos, H.
dc.contributor.authorJayne, C.
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionUniv Paulista UNIP
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2020-12-10T22:31:32Z
dc.date.available2020-12-10T22:31:32Z
dc.date.issued2013-01-01
dc.description.abstractPine is used primarily as a source of raw materials for the industries of lumber and laminated plates, resin, pulp and paper. Pine may be affected, from the nursery to adults, in plantations by pathogens such as fungi and/or pests. The aim of this work was to recognize patterns in images obtained from a thermal plants camera in pine. An Unmanned Aerial Vehicle with a thermal camera embedded was used to take video images of pine trees. The video was segmented in pictures and all the pictures were standardized to the same size 240 x 350px. The images were segmented and a two-layer neural network feed-forward and the Scaled Conjugate Gradient (SCG) algorithm were used. The results proved to be satisfactory, with most errors near zero.en
dc.description.affiliationUniv Sao Paulo, Inst Math & Comp Sci ICMC, Sao Paulo, Brazil
dc.description.affiliationUniv Paulista UNIP, Sao Paulo, Brazil
dc.description.affiliationUniv Estadual Paulista Julio Mesquita Filho UNESP, Sao Paulo, Brazil
dc.description.affiliationUnespUniv Estadual Paulista Julio Mesquita Filho UNESP, Sao Paulo, Brazil
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipIdFAPESP: 2012/08498-5
dc.description.sponsorshipId: 573963/2008-9
dc.description.sponsorshipId: 08/57870-9
dc.format.extent406-413
dc.identifier.citationEngineering Applications Of Neural Networks, Eann 2013, Pt I. Berlin: Springer-verlag Berlin, v. 383, p. 406-413, 2013.
dc.identifier.issn1865-0929
dc.identifier.urihttp://hdl.handle.net/11449/197436
dc.identifier.wosWOS:000345333800042
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofEngineering Applications Of Neural Networks, Eann 2013, Pt I
dc.sourceWeb of Science
dc.subjectArtificial neural networks
dc.subjectthermal images
dc.subjectPine tree and UAVs
dc.titlePattern Recognition in Thermal Images of Plants Pine Using Artificial Neural Networksen
dc.typeTrabalho apresentado em evento
dcterms.licensehttp://www.springer.com/open+access/authors+rights?SGWID=0-176704-12-683201-0
dcterms.rightsHolderSpringer
dspace.entity.typePublication
unesp.departmentProteção Vegetal - FCApt

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