Publicação: Pattern Recognition in Thermal Images of Plants Pine Using Artificial Neural Networks
dc.contributor.author | Bentivoglio Colturato, Adimara | |
dc.contributor.author | Benjamin Gomes, André | |
dc.contributor.author | Pigatto, Daniel Fernando | |
dc.contributor.author | Bentivoglio Colturato, Danielle | |
dc.contributor.author | Roschildt Pinto, Alex Sandro [UNESP] | |
dc.contributor.author | Castelo Branco, Luiz Henrique | |
dc.contributor.author | Furtado, Edson Luiz [UNESP] | |
dc.contributor.author | Lucas Jaquie Castelo Branco, Kalinka Regina | |
dc.contributor.institution | Universidade de São Paulo (USP) | |
dc.contributor.institution | Universidade Paulista (UNIP) | |
dc.contributor.institution | Universidade Estadual Paulista (UNESP) | |
dc.contributor.institution | Instituto Federal de Ciência e Tecnologia de São Paulo | |
dc.date.accessioned | 2022-04-29T08:44:51Z | |
dc.date.available | 2022-04-29T08:44:51Z | |
dc.date.issued | 2013-01-01 | |
dc.description.abstract | Pine 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. © Springer-Verlag Berlin Heidelberg 2013. | en |
dc.description.affiliation | Institute of Mathematics and Computing Sciences (ICMC) University of São Paulo (USP), São Carlos, São Paulo | |
dc.description.affiliation | Universidade Paulista (UNIP), Araraquara, São Paulo | |
dc.description.affiliation | Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP), Botucatu, São Paulo | |
dc.description.affiliation | Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP), São José do Rio Preto, São Paulo | |
dc.description.affiliation | Instituto Federal de Ciência e Tecnologia de São Paulo, Araraquara, São Paulo | |
dc.description.affiliationUnesp | Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP), Botucatu, São Paulo | |
dc.description.affiliationUnesp | Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP), São José do Rio Preto, São Paulo | |
dc.format.extent | 406-413 | |
dc.identifier | http://dx.doi.org/10.1007/978-3-642-41013-0_42 | |
dc.identifier.citation | Communications in Computer and Information Science, v. 383 CCIS, n. PART 1, p. 406-413, 2013. | |
dc.identifier.doi | 10.1007/978-3-642-41013-0_42 | |
dc.identifier.issn | 1865-0929 | |
dc.identifier.scopus | 2-s2.0-84904596388 | |
dc.identifier.uri | http://hdl.handle.net/11449/231336 | |
dc.language.iso | eng | |
dc.relation.ispartof | Communications in Computer and Information Science | |
dc.source | Scopus | |
dc.subject | Artificial neural networks | |
dc.subject | Pine tree and UAVs | |
dc.subject | thermal images | |
dc.title | Pattern Recognition in Thermal Images of Plants Pine Using Artificial Neural Networks | en |
dc.type | Trabalho apresentado em evento | |
dspace.entity.type | Publication | |
unesp.campus | Universidade Estadual Paulista (UNESP), Instituto de Química, Araraquara | pt |
unesp.department | Bioquímica e Tecnologia - IQ | pt |