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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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| Registros recuperados : 620 | |
| 101. |  | MORENO, B. M.; CRUVINEL, P. E. Characterization of an IoT Stereo Image Sensor System for Weed Control. In: INTERNATIONAL CONFERENCE ON ADVANCES IN SENSORS, ACTUATORS, METERING AND SENSING - ALLSENSORS 2023, 8., 2023, Venice, Italy. Proceedings... Wilmington, USA: IARIA, 2023. 7 p.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Instrumentação. |
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| 102. | | ALVES, G. M.; CRUVINEL, P. E. Big Data environment for agricultural soil analysis from CT digital images. In: INTERNATIONAL CONFERENCE ON SEMANTIC COMPUTING ? ICSC, 10., 2016, Laguna Hills, California, USA. Proceedings... Los Alamitos, California, EUA: IEEE, 2016. p. 429-431.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Instrumentação. |
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| 115. | | LAIA, M. A. M.; CRUVINEL, P. E. Filtragem de projeções tomográficas do solo utilizando Kalman e redes neurais em uma estimação conjunta. IN: BRAZILIAN CONFERENCE ON DYNAMICS, CONTROL AND APPLICATIONS - DINCON, 7.; CONGRESSO TEMÁTICO DE DINÃMICA, CONTROLE E APLICAÇÕES, 7., 2008, Presidente Prudente, SP. Poster... Presidente Prudente, SP: FCT-UNESP, 2008. 1 CD-ROM. p. 1-11. Organizado por J. M. Balthazar, G. N. Silva, M. Meneguette e M. Messias| Tipo: Artigo em Anais de Congresso / Nota Técnica |
| Biblioteca(s): Embrapa Instrumentação. |
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| 118. | | CORRÊA, E. G.; CRUVINEL, P. E. Efeitos positivos do componente arbóreo nos indicadores zootécnicos em sistemas de integração lavoura pecuária-floresta (ILPF) para animais de produção leiteira In: JORNADA CIENTÍFICA - EMBRAPA SÃO CARLOS, 14., 2022, São Carlos, SP. Anais... São Carlos: Embrapa Instrumentação: Embrapa Pecuária Sudeste, 2022. Editores técnicos: Cristiane Sanchez Farinas, Daniel Souza Corrêa, Maria Alice Martins, Maria Fernanda Berlingieri Durigan, Paulo Sérgio de Paula Herrmann Júnior. 20 p.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Instrumentação. |
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| 120. | | SHIBUYA, S. T.; CRUVINEL, P. E. Implementação de escala em tons de cinza em imagens tomográficas. In: REUNIÃO ANUAL DA SBPC, 41., jul. 1989, Fortaleza, CE. Ciência e Cultura, São Paulo, v.41, n.7, p.67, jul. 1989. Suplemento. Resumos. ref.01-A.8.| Biblioteca(s): Embrapa Instrumentação. |
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| Registros recuperados : 620 | |
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| Nenhum registro encontrado para a expressão de busca informada. |
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