Statistical learning mitigation of false positives from template-detected data in automated acoustic wildlife monitoring-Reference-Cited by-同舟云学术

Statistical learning mitigation of false positives from template-detected data in automated acoustic wildlife monitoring

Published:2019-05-06 Issue:3 Volume:29 Page:296-321
ISSN:0952-4622
Container-title:Bioacoustics
language:en
Short-container-title:Bioacoustics

Author:

Balantic Cathleen M.¹^ORCID,Donovan Therese M.²

Affiliation:

1. Vermont Cooperative Fish and Wildlife Research Unit, University of Vermont, Burlington, VT, USA

2. U.S. Geological Survey, Vermont Cooperative Fish and Wildlife Research Unit, Rubenstein School of Environment and Natural Resources, University of Vermont, Burlington, VT, USA

Funder

U.S. Bureau of Land Management

U.S. National Science Foundation IGERT Program

Publisher

Informa UK Limited

Subject

Ecology,Ecology, Evolution, Behavior and Systematics

Link

https://tandfonline.com/doi/pdf/10.1080/09524622.2019.1605309

Reference45 articles.

1. Automated classification of bird and amphibian calls using machine learning: A comparison of methods

2. Real-time bioacoustics monitoring and automated species identification

3. Improving geographically extensive acoustic survey designs for modeling species occurrence with imperfect detection and misidentification

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