A deep neural network for high‐throughput measurement of functional traits on museum skeletal specimens

A deep neural network for high‐throughput measurement of functional traits on museum skeletal specimens

Abstract Increasingly, natural history museum collections are being used to generate large‐scale morphological datasets to address a range of macroecological and macroevolutionary questions. One challenge to this approach is that large numbers of individuals either from a single species or from taxo...

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Bibliographic Details
Main Authors: Brian C. Weeks, Zhizhuo Zhou, Bruce K. O'Brien, Rachel Darling, Morgan Dean, Tiffany Dias, Gemmechu Hassena, Mingyu Zhang, David F. Fouhey
Format: Article
Language:English
Published: Wiley 2023-02-01
Series:Methods in Ecology and Evolution
Subjects:
computer vision
functional traits
macroecology
macroevolution
neural network
specimen‐based research
Online Access:https://doi.org/10.1111/2041-210X.13864

Internet

https://doi.org/10.1111/2041-210X.13864

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