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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Detalles Bibliográficos
Autores principales: Qiao, Yuhui, Liao, Qingxi, Zhang, Moran, Han, Binbin, Peng, Chengli, Huang, Zhenhao, Wang, Shaodong, Zhou, Guangsheng, Xu, Shengyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Plant Science
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10375295/
https://www.ncbi.nlm.nih.gov/pubmed/37521934
http://dx.doi.org/10.3389/fpls.2023.1188286

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10375295/
https://www.ncbi.nlm.nih.gov/pubmed/37521934
http://dx.doi.org/10.3389/fpls.2023.1188286

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