Identification of the variety of maize seeds based on hyperspectral images coupled with convolutional neural networks and subregional voting.

Zhou, Quan; Huang, Wenqian; Tian, Xi; Yang, Yi; Liang, Dong

Zhou, Quan; Huang, Wenqian; Tian, Xi; Yang, Yi; Liang, Dong.

Afiliación

Zhou Q; School of Electronics and Information Engineering, Anhui University, Hefei, China.
Huang W; Beijing Research Center of Intelligent Equipment for Agriculture, Beijing, China.
Tian X; National Research Center of Intelligent Equipment for Agriculture, Beijing, China.
Yang Y; Beijing Research Center of Intelligent Equipment for Agriculture, Beijing, China.
Liang D; National Research Center of Intelligent Equipment for Agriculture, Beijing, China.

J Sci Food Agric ; 101(11): 4532-4542, 2021 Aug 30.

Article en En | MEDLINE | ID: mdl-33452811

Asunto(s)

Semillas/química; Análisis Espectral/métodos; Zea mays/clasificación; Análisis Discriminante; Procesamiento de Imagen Asistido por Computador; Redes Neurales de la Computación; Semillas/clasificación; Semillas/crecimiento & desarrollo; Zea mays/química; Zea mays/crecimiento & desarrollo

Palabras clave

convolutional neural network; hyperspectral image; maize seed; subregional voting; variety identification

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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Semillas / Análisis Espectral / Zea mays Tipo de estudio: Diagnostic_studies / Evaluation_studies / Prognostic_studies Idioma: En Año: 2021 Tipo del documento: Article

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