An algorithm competition for automatic species identification from herbarium specimens

PREMISE: Plant biodiversity is threatened, yet many species remain undescribed. It is estimated that >50% of undescribed species have already been collected and are awaiting discovery in herbaria. Robust automatic species identification algorithms using machine learning could accelerate species d...

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Detalles Bibliográficos
Autores principales: Little, Damon P., Tulig, Melissa, Tan, Kiat Chuan, Liu, Yulong, Belongie, Serge, Kaeser‐Chen, Christine, Michelangeli, Fabián A., Panesar, Kiran, Guha, R.V., Ambrose, Barbara A.
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/PMC7328655/
https://www.ncbi.nlm.nih.gov/pubmed/32626608
http://dx.doi.org/10.1002/aps3.11365

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7328655/
https://www.ncbi.nlm.nih.gov/pubmed/32626608
http://dx.doi.org/10.1002/aps3.11365

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