Classification of apple tree disorders using Convolutional Neural Networks.

NACHTIGALL, L. G.; ARAUJO, R. M.; NACHTIGALL, G. R.

Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1052112

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DC Field	Value	Language
dc.contributor.author	NACHTIGALL, L. G.	pt_BR
dc.contributor.author	ARAUJO, R. M.	pt_BR
dc.contributor.author	NACHTIGALL, G. R.	pt_BR
dc.date.accessioned	2016-08-30T11:11:11Z	pt_BR
dc.date.available	2016-08-30T11:11:11Z	pt_BR
dc.date.created	2016-08-30	pt_BR
dc.date.issued	2016	pt_BR
dc.identifier.citation	In: 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.	pt_BR
dc.identifier.uri	http://www.alice.cnptia.embrapa.br/alice/handle/doc/1052112	pt_BR
dc.description	Abstract?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.	pt_BR
dc.language.iso	por	pt_BR
dc.rights	openAccess	pt_BR
dc.subject	Macieira	pt_BR
dc.subject	Redes neurais	pt_BR
dc.subject	Convolutional Neural Networks	pt_BR
dc.subject	Diseases	pt_BR
dc.subject	Nutritional deficiencies	pt_BR
dc.subject	Damage	pt_BR
dc.subject	Apple trees	pt_BR
dc.subject	Herbicide	pt_BR
dc.title	Classification of apple tree disorders using Convolutional Neural Networks.	pt_BR
dc.type	Artigo em anais e proceedings	pt_BR
dc.date.updated	2019-03-08T11:11:11Z	pt_BR
dc.subject.thesagro	Maca	pt_BR
riaa.ainfo.id	1052112	pt_BR
riaa.ainfo.lastupdate	2019-03-08 -03:00:00	pt_BR
dc.contributor.institution	GILMAR RIBEIRO NACHTIGALL, CNPUV.	pt_BR
Appears in Collections:	Artigo em anais de congresso (CNPUV)

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