A new method to control error rates in automated species identification with deep learning algorithms

Processing data from surveys using photos or videos remains a major bottleneck in ecology. Deep Learning Algorithms (DLAs) have been increasingly used to automatically identify organisms on images. However, despite recent advances, it remains difficult to control the error rate of such methods. Here...

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Detalles Bibliográficos
Autores principales: Villon, Sébastien, Mouillot, David, Chaumont, Marc, Subsol, Gérard, Claverie, Thomas, Villéger, Sébastien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334229/
https://www.ncbi.nlm.nih.gov/pubmed/32620873
http://dx.doi.org/10.1038/s41598-020-67573-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334229/
https://www.ncbi.nlm.nih.gov/pubmed/32620873
http://dx.doi.org/10.1038/s41598-020-67573-7

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