Use of Unmanned Aerial Vehicle Imagery and Deep Learning UNet to Extract Rice Lodging

Use of Unmanned Aerial Vehicle Imagery and Deep Learning UNet to Extract Rice Lodging

Rice lodging severely affects harvest yield. Traditional evaluation methods and manual on-site measurement are found to be time-consuming, labor-intensive, and cost-intensive. In this study, a new method for rice lodging assessment based on a deep learning UNet (U-shaped Network) architecture was pr...

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Bibliographic Details
Main Authors: Xin Zhao, Yitong Yuan, Mengdie Song, Yang Ding, Fenfang Lin, Dong Liang, Dongyan Zhang
Format: Article
Language:English
Published: MDPI AG 2019-09-01
Series:Sensors
Subjects:
rice lodging
UAV
UNet
semantic segmentation
assessment
<i>Oryza sativa</i> L.
Online Access:https://www.mdpi.com/1424-8220/19/18/3859

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https://www.mdpi.com/1424-8220/19/18/3859

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