Deep Learning: Individual Maize Segmentation From Terrestrial Lidar Data Using Faster R-CNN and Regional Growth Algorithms

Deep Learning: Individual Maize Segmentation From Terrestrial Lidar Data Using Faster R-CNN and Regional Growth Algorithms

The rapid development of light detection and ranging (Lidar) provides a promising way to obtain three-dimensional (3D) phenotype traits with its high ability of recording accurate 3D laser points. Recently, Lidar has been widely used to obtain phenotype data in the greenhouse and field with along ot...

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Bibliographic Details
Main Authors:	Shichao Jin, Yanjun Su, Shang Gao, Fangfang Wu, Tianyu Hu, Jin Liu, Wenkai Li, Dingchang Wang, Shaojiang Chen, Yuanxi Jiang, Shuxin Pang, Qinghua Guo
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2018-06-01
Series:	Frontiers in Plant Science
Subjects:	deep learning detection classification segmentation phenotype Lidar (light detection and ranging)
Online Access:	https://www.frontiersin.org/article/10.3389/fpls.2018.00866/full

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