dc.contributorUniversidade de São Paulo (USP)
dc.contributorUniversidade Paulista (UNIP)
dc.contributorUniversidade Estadual Paulista (UNESP)
dc.contributorInstituto Federal de Ciência e Tecnologia de São Paulo
dc.date.accessioned2022-04-29T08:44:51Z
dc.date.accessioned2022-12-20T03:14:43Z
dc.date.available2022-04-29T08:44:51Z
dc.date.available2022-12-20T03:14:43Z
dc.date.created2022-04-29T08:44:51Z
dc.date.issued2013-01-01
dc.identifierCommunications in Computer and Information Science, v. 383 CCIS, n. PART 1, p. 406-413, 2013.
dc.identifier1865-0929
dc.identifierhttp://hdl.handle.net/11449/231336
dc.identifier10.1007/978-3-642-41013-0_42
dc.identifier2-s2.0-84904596388
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5411470
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. © Springer-Verlag Berlin Heidelberg 2013.
dc.languageeng
dc.relationCommunications in Computer and Information Science
dc.sourceScopus
dc.subjectArtificial neural networks
dc.subjectPine tree and UAVs
dc.subjectthermal images
dc.titlePattern Recognition in Thermal Images of Plants Pine Using Artificial Neural Networks
dc.typeActas de congresos


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