Generating segmentation masks of herbarium specimens and a data set for training segmentation models using deep learning

PREMISE: Digitized images of herbarium specimens are highly diverse with many potential sources of visual noise and bias. The systematic removal of noise and minimization of bias must be achieved in order to generate biological insights based on the plants rather than the digitization and mounting p...

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Detalles Bibliográficos
Autores principales: White, Alexander E., Dikow, Rebecca B., Baugh, Makinnon, Jenkins, Abigail, Frandsen, Paul B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Application Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7328659/
https://www.ncbi.nlm.nih.gov/pubmed/32626607
http://dx.doi.org/10.1002/aps3.11352

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7328659/
https://www.ncbi.nlm.nih.gov/pubmed/32626607
http://dx.doi.org/10.1002/aps3.11352

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