Point clouds segmentation of rapeseed siliques based on sparse-dense point clouds mapping

In this study, we propose a high-throughput and low-cost automatic detection method based on deep learning to replace the inefficient manual counting of rapeseed siliques. First, a video is captured with a smartphone around the rapeseed plants in the silique stage. Feature point detection and matchi...

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Bibliografski detalji

Glavni autori:	Yuhui Qiao, Qingxi Liao, Moran Zhang, Binbin Han, Chengli Peng, Zhenhao Huang, Shaodong Wang, Guangsheng Zhou, Shengyong Xu
Format:	Artigo
Jezik:	Inglês
Izdano:	Frontiers Media S.A. 2023-07-01
Serija:	Frontiers in Plant Science
Teme:	rapeseed siliques 3D Reconstruction sparse-dense point clouds mapping point clouds segmentation silique recognition
Online pristup:	https://www.frontiersin.org/articles/10.3389/fpls.2023.1188286/full
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