Inside out: transforming images of lab-grown plants for machine learning applications in agriculture

INTRODUCTION: Machine learning tasks often require a significant amount of training data for the resultant network to perform suitably for a given problem in any domain. In agriculture, dataset sizes are further limited by phenotypical differences between two plants of the same genotype, often as a...

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Detalles Bibliográficos
Autores principales: Krosney, Alexander E., Sotoodeh, Parsa, Henry, Christopher J., Beck, Michael A., Bidinosti, Christopher P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10358354/
https://www.ncbi.nlm.nih.gov/pubmed/37483870
http://dx.doi.org/10.3389/frai.2023.1200977

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10358354/
https://www.ncbi.nlm.nih.gov/pubmed/37483870
http://dx.doi.org/10.3389/frai.2023.1200977

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