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Registro Completo
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Biblioteca(s): |
Embrapa Instrumentação. |
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Data corrente: |
25/10/2021 |
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Data da última atualização: |
09/06/2022 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
VERAMENDI, W. N. C.; CRUVINEL, P. E. |
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Afiliação: |
PAULO ESTEVAO CRUVINEL, CNPDIA. |
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Título: |
Algorithm for the countering maize plants based on UAV, digital image processing and semantic modeling. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
In: IEEE International Conference on Semantic Computing (ICSC), 15th, Laguna Hills, CA, USA, 2021. |
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Páginas: |
393-397 |
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DOI: |
10.1109/ICSC50631.2021.00072 |
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Idioma: |
Inglês |
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Conteúdo: |
With the need to increase agricultural production and to avoid loss, this paper presents the development of a new method for counting plants of maize in an agricultural field using spectral images obtained by an UAV, as well as digital processing and semantic modeling techniques. The method is based on the use of the Circular Hough Transform (CHT) in conjunction with the techniques of Backmapping, neighborhood analysis, and a classification of patterns. Both the supper vector machines (SVM) and the neural networks (NN) methods have been evaluated for the classification procedure. Besides„ using a computational environment for simulation, previous results have been obtained, i.e., showing not only the usefulness of the direct measures but also an automatic way for the plants identification, counting and height determination of the planted maize. Also, the establishment of a friendly interface has been carried out, which allows the monitoring of the phenological phases involved in the stages of the maize cultivation. |
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Palavras-Chave: |
Hough Transform; Image Processing; Semantic Decision Making. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 01676nam a2200181 a 4500
001 2135520
005 2022-06-09
008 2021 bl uuuu u00u1 u #d
024 7 $a10.1109/ICSC50631.2021.00072$2DOI
100 1 $aVERAMENDI, W. N. C.
245 $aAlgorithm for the countering maize plants based on UAV, digital image processing and semantic modeling.$h[electronic resource]
260 $aIn: IEEE International Conference on Semantic Computing (ICSC), 15th, Laguna Hills, CA, USA$c2021
300 $a393-397
520 $aWith the need to increase agricultural production and to avoid loss, this paper presents the development of a new method for counting plants of maize in an agricultural field using spectral images obtained by an UAV, as well as digital processing and semantic modeling techniques. The method is based on the use of the Circular Hough Transform (CHT) in conjunction with the techniques of Backmapping, neighborhood analysis, and a classification of patterns. Both the supper vector machines (SVM) and the neural networks (NN) methods have been evaluated for the classification procedure. Besides„ using a computational environment for simulation, previous results have been obtained, i.e., showing not only the usefulness of the direct measures but also an automatic way for the plants identification, counting and height determination of the planted maize. Also, the establishment of a friendly interface has been carried out, which allows the monitoring of the phenological phases involved in the stages of the maize cultivation.
653 $aHough Transform
653 $aImage Processing
653 $aSemantic Decision Making
700 1 $aCRUVINEL, P. E.
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