Accurate Imputation of Greenhouse Environment Data for Data Integrity Utilizing Two-Dimensional Convolutional Neural Networks

Greenhouses require accurate and reliable data to interpret the microclimate and maximize resource use efficiency. However, greenhouse conditions are harsh for electrical sensors collecting environmental data. Convolutional neural networks (ConvNets) enable complex interpretation by multiplying the...

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Detalles Bibliográficos
Autores principales: Moon, Taewon, Lee, Joon Woo, Son, Jung Eek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8003888/
https://www.ncbi.nlm.nih.gov/pubmed/33804781
http://dx.doi.org/10.3390/s21062187

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8003888/
https://www.ncbi.nlm.nih.gov/pubmed/33804781
http://dx.doi.org/10.3390/s21062187

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