Cargando…
Correction: YOLO POD: a fast and accurate multi-task model for dense Soybean Pod counting
Autores principales: | Xiang, Shuai, Wang, Siyu, Xu, Mei, Wang, Wenyan, Liu, Weiguo |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10176821/ https://www.ncbi.nlm.nih.gov/pubmed/37170097 http://dx.doi.org/10.1186/s13007-023-01013-1 |
Ejemplares similares
-
YOLO POD: a fast and accurate multi-task model for dense Soybean Pod counting
por: Xiang, Shuai, et al.
Publicado: (2023) -
Pod power: Soybean pod and seed photosynthesis contributes to yield
por: Burgess, Alexandra J, et al.
Publicado: (2023) -
Mapping and use of QTLs controlling pod dehiscence in soybean
por: Funatsuki, Hideyuki, et al.
Publicado: (2012) -
Segmentation and Phenotype Calculation of Rapeseed Pods Based on YOLO v8 and Mask R-Convolution Neural Networks
por: Wang, Nan, et al.
Publicado: (2023) -
What the F‐POD? Comparing the F‐POD and C‐POD for monitoring of harbor porpoise (Phocoena phocoena)
por: Todd, Nicole Rose Eileen, et al.
Publicado: (2023)