dc.contributorAeronaut Inst Technol
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2019-10-04T11:55:58Z
dc.date.accessioned2022-12-19T17:52:25Z
dc.date.available2019-10-04T11:55:58Z
dc.date.available2022-12-19T17:52:25Z
dc.date.created2019-10-04T11:55:58Z
dc.date.issued2017-01-01
dc.identifierProceedings 2017 International Conference On Computational Science And Computational Intelligence (csci). New York: Ieee, p. 456-462, 2017.
dc.identifierhttp://hdl.handle.net/11449/184224
dc.identifier10.1109/CSCI.2017.77
dc.identifierWOS:000455029500080
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5365279
dc.description.abstractA methodology was developed in this work for the automatic counting of individual seedlings in plantations of Eucalyptus spp from high definition photographs with the help of Scientific Python Libraries from literature. The problem to be investigated was presented and two different ways of solving it were discussed together with their implications. With the algorithm properly validated on training data, an actual business case of seedlings detection and counting out of a mosaic aerial image was proposed as testing data. The high-definition pictures were taken by multispectral sensor onboard an UAV from an Eucalyptus spp plantation stand of approximately 25 hectares and provided by Eldorado Brasil. The results were considered very encouraging, stimulating future works in this line of research.
dc.languageeng
dc.publisherIeee
dc.relationProceedings 2017 International Conference On Computational Science And Computational Intelligence (csci)
dc.rightsAcesso aberto
dc.sourceWeb of Science
dc.subjectEucalyptus spp.
dc.subjectPython
dc.subjectImage processing
dc.subjectBinarized classification
dc.subjectPrecision agriculture
dc.titleHSV and NDVI Color Space Analysis and Sampling Procedure for Counting of Seedlings in Eucalyptus spp Plantations from High Definition Aerial Images
dc.typeActas de congresos


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