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...

書誌詳細
出版年:	Frontiers in Plant Science
主要な著者:	Yuhui Qiao, Qingxi Liao, Moran Zhang, Binbin Han, Chengli Peng, Zhenhao Huang, Shaodong Wang, Guangsheng Zhou, Shengyong Xu
フォーマット:	論文
言語:	英語
出版事項:	Frontiers Media S.A. 2023-07-01
主題:	rapeseed siliques 3D Reconstruction sparse-dense point clouds mapping point clouds segmentation silique recognition
オンライン･アクセス:	https://www.frontiersin.org/articles/10.3389/fpls.2023.1188286/full

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