Classification of apple tree disorders using Convolutional Neural Networks.

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dc.contributorGILMAR RIBEIRO NACHTIGALL, CNPUV.
dc.creatorNACHTIGALL, L. G.
dc.creatorARAUJO, R. M.
dc.creatorNACHTIGALL, G. R.
dc.date2016-08-30T11:11:11Z
dc.date2016-08-30T11:11:11Z
dc.date2016-08-30
dc.date2016
dc.date2019-03-08T11:11:11Z
dc.date.accessioned2026-07-07T11:24:58Z
dc.descriptionAbstract?This paper studies the use of Convolutional Neural Networks to automatically detect and classify diseases, nutritional deficiencies and damage by herbicides on apple trees from images of their leaves. This task is fundamental to guarantee a high quality of the resulting yields and is currently largely performed by experts in the field, which can severely limit scale and add to costs. By using a novel data set containing labeled examples consisting of 2539 images from 6 known disorders, we show that trained Convolutional Neural Networks are able to match or outperform experts in this task, achieving a 97.3% accuracy on a hold-out set.
dc.identifierIn: INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENSE, 28., 2016, San Jose, United States. Anais...San Jose, United States: IEEE, Paper Submission 127, p. 472-476, 2016.
dc.identifierhttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1052112
dc.identifier.urihttp://hdl.handle.net/123456789/506947
dc.languagepor
dc.rightsopenAccess
dc.subjectMacieira
dc.subjectRedes neurais
dc.subjectConvolutional Neural Networks
dc.subjectDiseases
dc.subjectNutritional deficiencies
dc.subjectDamage
dc.subjectApple trees
dc.subjectHerbicide
dc.subjectMaca
dc.titleClassification of apple tree disorders using Convolutional Neural Networks.
dc.typeArtigo em anais e proceedings

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