Author(s): Bentivoglio Colturato, Adimara ; Benjamin Gomes, André ; Pigatto, Daniel Fernando ; Bentivoglio Colturato, Danielle ; Roschildt Pinto, Alex Sandro [UNESP] ; Castelo Branco, Luiz Henrique ; Furtado, Edson Luiz [UNESP] ; Lucas Jaquie Castelo Branco, Kalinka Regina
Date: 2022
Persistent ID: http://hdl.handle.net/11449/231336
Origin: Oasisbr
Subject(s): Artificial neural networks; Pine tree and UAVs; thermal images
Made available in DSpace on 2022-04-29T08:44:51Z (GMT). No. of bitstreams: 0 Previous issue date: 2013-01-01
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.
Institute of Mathematics and Computing Sciences (ICMC) University of São Paulo (USP), São Carlos, São Paulo
Universidade Paulista (UNIP), Araraquara, São Paulo
Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP), Botucatu, São Paulo
Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP), São José do Rio Preto, São Paulo
Instituto Federal de Ciência e Tecnologia de São Paulo, Araraquara, São Paulo
Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP), Botucatu, São Paulo
Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP), São José do Rio Preto, São Paulo
