Rapeseed Stand Count Estimation at Leaf Development Stages With UAV Imagery and Convolutional Neural Networks

Rapeseed Stand Count Estimation at Leaf Development Stages With UAV Imagery and Convolutional Neural Networks

Rapeseed is an important oil crop in China. Timely estimation of rapeseed stand count at early growth stages provides useful information for precision fertilization, irrigation, and yield prediction. Based on the nature of rapeseed, the number of tillering leaves is strongly related to its growth st...

Full description

Bibliographic Details
Main Authors: Jian Zhang, Biquan Zhao, Chenghai Yang, Yeyin Shi, Qingxi Liao, Guangsheng Zhou, Chufeng Wang, Tianjin Xie, Zhao Jiang, Dongyan Zhang, Wanneng Yang, Chenglong Huang, Jing Xie
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-06-01
Series:Frontiers in Plant Science
Subjects:
stand counting
field-based phenotyping
optimal observation timing
convolutional neural network
precision agriculture
Online Access:https://www.frontiersin.org/article/10.3389/fpls.2020.00617/full

Internet

https://www.frontiersin.org/article/10.3389/fpls.2020.00617/full

Similar Items