Deep Learning for Non-Invasive Diagnosis of Nutrient Deficiencies in Sugar Beet Using RGB Images
In order to enable timely actions to prevent major losses of crops caused by lack of nutrients and, hence, increase the potential yield throughout the growing season while at the same time prevent excess fertilization with detrimental environmental consequences, early, non-invasive, and on-site dete...
Main Authors: | Jinhui Yi, Lukas Krusenbaum, Paula Unger, Hubert Hüging, Sabine J. Seidel, Gabriel Schaaf, Juergen Gall |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-10-01
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Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/20/20/5893 |
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