Conference Abstract
Biodiversity Information Science and Standards 3: e37479
https://doi.org/10.3897/biss.3.37479 (26 Jun 2019)
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Biodiversity Information Science and Standards 3: e37479
doi: 10.3897/biss.3.37479
Received: 18 Jun 2019 | Published: 26 Jun 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 - 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
http://www.alexwhitebiology.com/
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Rebecca B Dikow
Data Science Lab, Smithsonian Institution, Washington DC, United States of America
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Makinnon Baugh
Brigham Young University, Provo UT, United States of America
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Abby Jenkins
Brigham Young University, Provo UT, United States of America
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Paul B Frandsen
Brigham Young University, Provo UT, United States of America
Rutgers University, New Brunswick, NJ, United States of America
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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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