Automatic Wheat Lodging Detection and Mapping in Aerial Imagery to Support High-Throughput Phenotyping and In-Season Crop Management

Automatic Wheat Lodging Detection and Mapping in Aerial Imagery to Support High-Throughput Phenotyping and In-Season Crop Management

Latest advances in unmanned aerial vehicle (UAV) technology and convolutional neural networks (CNNs) allow us to detect crop lodging in a more precise and accurate way. However, the performance and generalization of a model capable of detecting lodging when the plants may show different spectral and...

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Bibliographic Details
Main Authors: Biquan Zhao, Jiating Li, P. Stephen Baenziger, Vikas Belamkar, Yufeng Ge, Jian Zhang, Yeyin Shi
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Agronomy
Subjects:
spatial data analysis
digital agriculture
decision support
deep learning
UAV
remote sensing
Online Access:https://www.mdpi.com/2073-4395/10/11/1762

Internet

https://www.mdpi.com/2073-4395/10/11/1762

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