A review of supervised learning methods for classifying animal behavioural states from environmental features-Reference-Cited by-同舟云学术

A review of supervised learning methods for classifying animal behavioural states from environmental features

Published:2022-11-16 Issue:1 Volume:14 Page:189-202
ISSN:2041-210X
Container-title:Methods in Ecology and Evolution
language:en
Short-container-title:Methods Ecol Evol

Author:

Bergen Silas¹^ORCID,Huso Manuela M.²³^ORCID,Duerr Adam E.⁴⁵⁶^ORCID,Braham Melissa A.⁶^ORCID,Schmuecker Sara⁷,Miller Tricia A.⁵⁶^ORCID,Katzner Todd E.⁸^ORCID

Affiliation:

1. Department of Mathematics and Statistics Winona State University Winona Minnesota USA

2. U.S. Geological Survey Forest and Rangeland Ecosystem Science Center Corvallis Oregon USA

3. Statistics Department Oregon State University Corvallis Oregon USA

4. Bloom Research Inc Los Angeles California USA

5. West Virginia University Morgantown West Virginia USA

6. Conservation Science Global, Inc West Cape May New Jersey USA

7. U.S. Fish and Wildlife Service Illinois‐Iowa Field Office Moline Illinois USA

8. U.S. Geological Survey Forest and Rangeland Ecosystem Science Center Boise Idaho USA

Funder

American Eagle Foundation

U.S. Fish and Wildlife Service

Publisher

Wiley

Subject

Ecological Modeling,Ecology, Evolution, Behavior and Systematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.14019

Reference29 articles.

1. Classifying behavior from short‐interval biologging data: An example with GPS tracking of birds

2. Behaviour Classification on Giraffes (Giraffa camelopardalis) Using Machine Learning Algorithms on Triaxial Acceleration Data of Two Commonly Used GPS Devices and Its Possible Application for Their Management and Conservation

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