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Registro Completo |
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Biblioteca(s): |
Embrapa Instrumentação. |
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Data corrente: |
09/06/2022 |
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Data da última atualização: |
23/01/2024 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
NEVES, R. A.; CRUVINEL, P. E. |
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Afiliação: |
PAULO ESTEVAO CRUVINEL, CNPDIA. |
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Título: |
Application of image processing and advanced intelligent computing for determining stage of Asian rust in soybean plants. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
In: IEEE International Conference on Semantic Computing (ICSC), 16th, Laguna Hills, CA, USA, 2022. |
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Páginas: |
280 - 286 |
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ISBN: |
978-1-6654-3418-8 |
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ISSN: |
2325-6516 |
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DOI: |
10.1109/ICSC52841.2022.00053 |
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Idioma: |
Inglês |
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Conteúdo: |
This paper presents a new method that uses the advanced techniques of digital image processing and computational intelligence for monitoring and identifying the stages of Asian rust (Phakopsora pachyrhizi) in soybean plants Glycine max (L.) Merril). Its establishment included organization and structuring of digital images of soybean plant leaves, image preprocessing steps, and segmentation based on the phenomenology of the disease development process with a semantics approach involving agricultural evaluation. The method also required recognition of the patterns appearing on leaves due to the presence of the disease as well as machine learning using a support vector machine for the classification and interpretation of the stages and their evolutions. For the stage of pattern recognition, the techniques of feature extraction scaleinvariant feature transform, Hu invariant moments, and histogram of oriented gradients were used and principal component analysis was conducted for the dimensionality reduction of the integrated vector of the features. The results of the application of the method showed potential for the monitoring and identification of the stages of the disease for determining the subsidies in the decision-making of production systems by agricultural producers |
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Palavras-Chave: |
Asian soybean rust; Image processing; Machine learning; Semantic segmentation. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02041nam a2200217 a 4500
001 2143890
005 2024-01-23
008 2022 bl uuuu u01u1 u #d
020 $a978-1-6654-3418-8
022 $a2325-6516
024 7 $a10.1109/ICSC52841.2022.00053$2DOI
100 1 $aNEVES, R. A.
245 $aApplication of image processing and advanced intelligent computing for determining stage of Asian rust in soybean plants.$h[electronic resource]
260 $aIn: IEEE International Conference on Semantic Computing (ICSC), 16th, Laguna Hills, CA, USA$c2022
300 $a280 - 286
520 $aThis paper presents a new method that uses the advanced techniques of digital image processing and computational intelligence for monitoring and identifying the stages of Asian rust (Phakopsora pachyrhizi) in soybean plants Glycine max (L.) Merril). Its establishment included organization and structuring of digital images of soybean plant leaves, image preprocessing steps, and segmentation based on the phenomenology of the disease development process with a semantics approach involving agricultural evaluation. The method also required recognition of the patterns appearing on leaves due to the presence of the disease as well as machine learning using a support vector machine for the classification and interpretation of the stages and their evolutions. For the stage of pattern recognition, the techniques of feature extraction scaleinvariant feature transform, Hu invariant moments, and histogram of oriented gradients were used and principal component analysis was conducted for the dimensionality reduction of the integrated vector of the features. The results of the application of the method showed potential for the monitoring and identification of the stages of the disease for determining the subsidies in the decision-making of production systems by agricultural producers
653 $aAsian soybean rust
653 $aImage processing
653 $aMachine learning
653 $aSemantic segmentation
700 1 $aCRUVINEL, P. E.
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Registro original: |
Embrapa Instrumentação (CNPDIA) |
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Biblioteca |
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Origem |
Tipo/Formato |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Arroz e Feijão. Para informações adicionais entre em contato com cnpaf.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
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Data corrente: |
23/03/2004 |
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Data da última atualização: |
23/03/2004 |
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Autoria: |
MAGALHÃES JUNIOR, A. M. de; FRANCO, D. F.; FAGUNDES, P. R. R.; TERRES, A. L.; ANDRES, A.; RANGEL, P. H. N.; SILVA, M. P. |
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Título: |
Avaliação de famílias So:2 oriundas do programa seleção recorrente de arroz irrigado da Embrapa - safra 2001/2002. |
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Ano de publicação: |
2002 |
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Fonte/Imprenta: |
In: CONGRESSO DA CADEIA PRODUTIVA DE ARROZ, 1.; REUNIÃO NACIONAL DE PESQUISA DE ARROZ - RENAPA, 7., 2002, Florianópolis. Anais... Santo Antônio de Goiás: Embrapa Arroz e Feijão, 2002. |
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Páginas: |
p. 119-122. |
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Série: |
(Embrapa Arroz e Feijão. Documentos, 134). |
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Idioma: |
Português |
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Palavras-Chave: |
Avaliação; Irrigado. |
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Thesagro: |
Arroz; Seleção Recorrente. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 00913naa a2200253 a 4500
001 1212027
005 2004-03-23
008 2002 bl uuuu u00u1 u #d
100 1 $aMAGALHÃES JUNIOR, A. M. de
245 $aAvaliação de famílias So$b2 oriundas do programa seleção recorrente de arroz irrigado da Embrapa - safra 2001/2002.
260 $c2002
300 $ap. 119-122.
490 $a(Embrapa Arroz e Feijão. Documentos, 134).
650 $aArroz
650 $aSeleção Recorrente
653 $aAvaliação
653 $aIrrigado
700 1 $aFRANCO, D. F.
700 1 $aFAGUNDES, P. R. R.
700 1 $aTERRES, A. L.
700 1 $aANDRES, A.
700 1 $aRANGEL, P. H. N.
700 1 $aSILVA, M. P.
773 $tIn: CONGRESSO DA CADEIA PRODUTIVA DE ARROZ, 1.; REUNIÃO NACIONAL DE PESQUISA DE ARROZ - RENAPA, 7., 2002, Florianópolis. Anais... Santo Antônio de Goiás: Embrapa Arroz e Feijão, 2002.
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Embrapa Arroz e Feijão (CNPAF) |
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