Estimation of the Botanical Composition of Clover-Grass Leys from RGB Images Using Data Simulation and Fully Convolutional Neural Networks

Optimal fertilization of clover-grass fields relies on knowledge of the clover and grass fractions. This study shows how knowledge can be obtained by analyzing images collected in fields automatically. A fully convolutional neural network was trained to create a pixel-wise classification of clover,...

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Detalles Bibliográficos
Autores principales: Skovsen, Søren, Dyrmann, Mads, Mortensen, Anders Krogh, Steen, Kim Arild, Green, Ole, Eriksen, Jørgen, Gislum, René, Jørgensen, Rasmus Nyholm, Karstoft, Henrik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751073/
https://www.ncbi.nlm.nih.gov/pubmed/29258215
http://dx.doi.org/10.3390/s17122930

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751073/
https://www.ncbi.nlm.nih.gov/pubmed/29258215
http://dx.doi.org/10.3390/s17122930

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