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

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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Bibliographic Details
Main Authors:	Taewon Moon, Joon Woo Lee, Jung Eek Son
Format:	Article
Language:	English
Published:	MDPI AG 2021-03-01
Series:	Sensors
Subjects:	artificial intelligence deep learning interpolation machine learning plant environment
Online Access:	https://www.mdpi.com/1424-8220/21/6/2187

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