Millimeter-Level Plant Disease Detection From Aerial Photographs via Deep Learning and Crowdsourced Data

Millimeter-Level Plant Disease Detection From Aerial Photographs via Deep Learning and Crowdsourced Data

Computer vision models that can recognize plant diseases in the field would be valuable tools for disease management and resistance breeding. Generating enough data to train these models is difficult, however, since only trained experts can accurately identify symptoms. In this study, we describe an...

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Bibliographic Details
Main Authors: Tyr Wiesner-Hanks, Harvey Wu, Ethan Stewart, Chad DeChant, Nicholas Kaczmar, Hod Lipson, Michael A. Gore, Rebecca J. Nelson
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-12-01
Series:Frontiers in Plant Science
Subjects:
phenotyping
unmanned aerial vehicles
plant disease
deep learning
machine learning
crowdsourcing
Online Access:https://www.frontiersin.org/article/10.3389/fpls.2019.01550/full

Internet

https://www.frontiersin.org/article/10.3389/fpls.2019.01550/full

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