Maximizing citizen scientists’ contribution to automated species recognition

ABSTRACT: Technological advances and data availability have enabled artificial intelligence-driven tools that can increasingly successfully assist in identifying species from images. Especially within citizen science, an emerging source of information filling the knowledge gaps needed to solve the biodiversity crisis, such tools can allow participants to recognize and report more poorly known species. This can be an important tool in addressing the substantial taxonomic bias in biodiversity data, where broadly recognized, charismatic species are highly over-represented. Meanwhile, the recognition models are trained using the same biased data, so it is important to consider what additional images are needed to improve recognition models. In this study, we investigated how the amount of training data

SUBMITTER: Koch W 

PROVIDER: S-EPMC9090737 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature