Classification of apple tree disorders using Convolutional Neural Networks.

Detalhes bibliográficos
Autor(a) principal: NACHTIGALL, L. G.
Data de Publicação: 2016
Outros Autores: ARAUJO, R. M., NACHTIGALL, G. R.
Idioma: por
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1052112
Resumo: 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.
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spelling Classification of apple tree disorders using Convolutional Neural Networks.MacieiraRedes neuraisConvolutional Neural NetworksDiseasesNutritional deficienciesDamageApple treesHerbicideMacaAbstract?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.GILMAR RIBEIRO NACHTIGALL, CNPUV.NACHTIGALL, L. G.ARAUJO, R. M.NACHTIGALL, G. R.2016-08-30T11:11:11Z2016-08-30T11:11:11Z2016-08-3020162019-03-08T11:11:11ZArtigo em anais e proceedingsinfo:eu-repo/semantics/publishedVersionIn: 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.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1052112porinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2017-08-16T04:17:20Zoai:www.alice.cnptia.embrapa.br:doc/1052112Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542017-08-16T04:17:20Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Classification of apple tree disorders using Convolutional Neural Networks.
title Classification of apple tree disorders using Convolutional Neural Networks.
spellingShingle Classification of apple tree disorders using Convolutional Neural Networks.
NACHTIGALL, L. G.
Macieira
Redes neurais
Convolutional Neural Networks
Diseases
Nutritional deficiencies
Damage
Apple trees
Herbicide
Maca
title_short Classification of apple tree disorders using Convolutional Neural Networks.
title_full Classification of apple tree disorders using Convolutional Neural Networks.
title_fullStr Classification of apple tree disorders using Convolutional Neural Networks.
title_full_unstemmed Classification of apple tree disorders using Convolutional Neural Networks.
title_sort Classification of apple tree disorders using Convolutional Neural Networks.
author NACHTIGALL, L. G.
author_facet NACHTIGALL, L. G.
ARAUJO, R. M.
NACHTIGALL, G. R.
author_role author
author2 ARAUJO, R. M.
NACHTIGALL, G. R.
author2_role author
author
dc.contributor.none.fl_str_mv GILMAR RIBEIRO NACHTIGALL, CNPUV.
dc.contributor.author.fl_str_mv NACHTIGALL, L. G.
ARAUJO, R. M.
NACHTIGALL, G. R.
dc.subject.por.fl_str_mv Macieira
Redes neurais
Convolutional Neural Networks
Diseases
Nutritional deficiencies
Damage
Apple trees
Herbicide
Maca
topic Macieira
Redes neurais
Convolutional Neural Networks
Diseases
Nutritional deficiencies
Damage
Apple trees
Herbicide
Maca
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.
publishDate 2016
dc.date.none.fl_str_mv 2016-08-30T11:11:11Z
2016-08-30T11:11:11Z
2016-08-30
2016
2019-03-08T11:11:11Z
dc.type.driver.fl_str_mv Artigo em anais e proceedings
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv 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.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1052112
identifier_str_mv 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.
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1052112
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
collection Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
repository.name.fl_str_mv Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv cg-riaa@embrapa.br
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