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

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....

Full description

Bibliographic Details
Main Authors: Andrew M. Durso, Gokula Krishnan Moorthy, Sharada P. Mohanty, Isabelle Bolon, Marcel Salathé, Rafael Ruiz de Castañeda
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-04-01
Series:Frontiers in Artificial Intelligence
Subjects:
fine-grained image classification
crowd-sourcing
reptiles
epidemiology
biodiversity
Online Access:https://www.frontiersin.org/articles/10.3389/frai.2021.582110/full

Internet

https://www.frontiersin.org/articles/10.3389/frai.2021.582110/full

Similar Items