HyperSeed: An End-to-End Method to Process Hyperspectral Images of Seeds.

Gao, Tian; Chandran, Anil Kumar Nalini; Paul, Puneet; Walia, Harkamal; Yu, Hongfeng

Gao, Tian; Chandran, Anil Kumar Nalini; Paul, Puneet; Walia, Harkamal; Yu, Hongfeng.

Afiliación

Gao T; School of Computing, University of Nebraska-Lincoln, Lincoln, NE 68588, USA.
Chandran AKN; Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68583, USA.
Paul P; Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68583, USA.
Walia H; Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68583, USA.
Yu H; School of Computing, University of Nebraska-Lincoln, Lincoln, NE 68588, USA.

Sensors (Basel) ; 21(24)2021 Dec 08.

Article en En | MEDLINE | ID: mdl-34960287

Asunto(s)

Redes Neurales de la Computación; Oryza; Análisis Espectral; Máquina de Vectores de Soporte

Palabras clave

3D convolutional neural network (CNN); high-throughput seed phenotyping; hyperspectral analysis; hyperspectral imaging system; light gradient boosting machine (LightGBM); phenotyping software; seed heat stress; support vector machine (SVM)

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Oryza / Redes Neurales de la Computación Idioma: En Revista: Sensors (Basel) Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza

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