Going deeper in the automated identification of Herbarium specimens

Bonnet, Pierre 
Mata-Montero, Erick
Joly, Alexis 
Goeau, Herve 
Carranza-Rojas, José

2017-08-28T17:02:41Z

1471-2148
Jose Carranza-Rojas, Herve Goeau, Pierre Bonnet V, Erick Mata-Montero, Alexis Joly. 2017. "Going deeper in the automated identification of Herbarium specimens" BMC Evolutionary Biology. volumen 17, número 181.

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Hundreds of herbarium collections have accumulated a valuable heritage and knowledge of plants over several centuries. Recent initiatives started ambitious preservation plans to digitize this information and make it available to botanists and the general public through web portals. However, thousands of sheets are still unidentified at the species level while numerous sheets should be reviewed and updated following more recent taxonomic knowledge. These annotations and revisions require an unrealistic amount of work for botanists to carry out in a reasonable time. Computer vision and machine learning approaches applied to herbarium sheets are promising but are still not well studied compared to automated species identification from leaf scans or pictures of plants in the field.

Research Subject Categories::TECHNOLOGY::Information technology::Image analysis; Research Subject Categories::NATURAL SCIENCES::Biology::Organism biology::Plant physiology; Aprendizaje; Identificación; Visión artificial; Botánica; Informática; Biodiversidad;