Conference Abstract
Biodiversity Information Science and Standards 3: e37559
https://doi.org/10.3897/biss.3.37559 (02 Jul 2019)
https://doi.org/10.3897/biss.3.37559 (02 Jul 2019)
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Biodiversity Information Science and Standards 3: e37559
doi:
10.3897/biss.3.37559
Received:
20 Jun 2019 | Published:
02 Jul 2019
This article is part of:
SS86 - Machine learning: an emerging toolkit for biodiversity science using museum collections
Edited by Paul Frandsen, Rebecca Dikow, Mike Trizna, Alex White
Authors
Alexander E White 
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- Corresponding author
Data Science Lab, Smithsonian Institution, Washington, DC, United States of America
National Museum of Natural History, Smithsonian Institution, Washington DC, United States of America
Data Science Lab, Smithsonian Institution, Washington, DC, United States of America
Smithsonian Institution, Washington, United States of America
Brigham Young University, Provo, UT, United States of America
Rutgers University, New Brunswick, NJ, United States of America
National Museum of Natural History, Smithsonian Institution, Washington DC, United States of America
Data Science Lab, Smithsonian Institution, Washington, DC, United States of America
National Museum of Natural History, Smithsonian Institution, Washington DC, United States of America
Conflict of interest
The authors have declared that no competing interests exist.
This is an open access article distributed under the terms of the CC0 Public Domain Dedication.
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