High-throughput soybean seeds phenotyping with convolutional neural networks and transfer learning

BACKGROUND: Effective soybean seed phenotyping demands large-scale accurate quantities of morphological parameters. The traditional manual acquisition of soybean seed morphological phenotype information is error-prone, and time-consuming, which is not feasible for large-scale collection. The segment...

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Detalles Bibliográficos
Autores principales: Yang, Si, Zheng, Lihua, He, Peng, Wu, Tingting, Sun, Shi, Wang, Minjuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097802/
https://www.ncbi.nlm.nih.gov/pubmed/33952294
http://dx.doi.org/10.1186/s13007-021-00749-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097802/
https://www.ncbi.nlm.nih.gov/pubmed/33952294
http://dx.doi.org/10.1186/s13007-021-00749-y

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