Universal detection of curved rice panicles in complex environments using aerial images and improved YOLOv4 model

Accurate and rapid identification of the effective number of panicles per unit area is crucial for the assessment of rice yield. As part of agricultural development, manual observation of effective panicles in the paddy field is being replaced by unmanned aerial vehicle (UAV) imaging combined with t...

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Detalles Bibliográficos
Autores principales: Sun, Boteng, Zhou, Wei, Zhu, Shilin, Huang, Song, Yu, Xun, Wu, Zhenyuan, Lei, Xiaolong, Yin, Dameng, Xia, Haixiao, Chen, Yong, Deng, Fei, Tao, Youfeng, Cheng, Hong, Jin, Xiuliang, Ren, Wanjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Plant Science
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9676644/
https://www.ncbi.nlm.nih.gov/pubmed/36420030
http://dx.doi.org/10.3389/fpls.2022.1021398

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9676644/
https://www.ncbi.nlm.nih.gov/pubmed/36420030
http://dx.doi.org/10.3389/fpls.2022.1021398

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