Supervised Learning Computer Vision Benchmark for Snake Species Identification From Photographs: Implications for Herpetology and Global Health

We trained a computer vision algorithm to identify 45 species of snakes from photos and compared its performance to that of humans. Both human and algorithm performance is substantially better than randomly guessing (null probability of guessing correctly given 45 classes = 2.2%). Some species (e.g....

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Detalles Bibliográficos
Autores principales: Durso, Andrew M., Moorthy, Gokula Krishnan, Mohanty, Sharada P., Bolon, Isabelle, Salathé, Marcel, Ruiz de Castañeda, Rafael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8093445/
https://www.ncbi.nlm.nih.gov/pubmed/33959704
http://dx.doi.org/10.3389/frai.2021.582110

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8093445/
https://www.ncbi.nlm.nih.gov/pubmed/33959704
http://dx.doi.org/10.3389/frai.2021.582110

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