Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Use of object detection in camera trap image identification: assessing a method to rapidly and accurately classify human and animal detections for research and application in recreation ecology

View ORCID ProfileMitchell Fennell, View ORCID ProfileChristopher Beirne, View ORCID ProfileA. Cole Burton
doi: https://doi.org/10.1101/2022.01.14.476404
Mitchell Fennell
ADepartment of Forest Resources Management, University of British Columbia, 2424 Main Mall, V5T 1Z4, Vancouver, BC, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Mitchell Fennell
  • For correspondence: mitchell.fennell@gmail.com
Christopher Beirne
ADepartment of Forest Resources Management, University of British Columbia, 2424 Main Mall, V5T 1Z4, Vancouver, BC, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Christopher Beirne
A. Cole Burton
ADepartment of Forest Resources Management, University of British Columbia, 2424 Main Mall, V5T 1Z4, Vancouver, BC, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for A. Cole Burton
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Data/Code
  • Preview PDF
Loading

Article Information

doi 
https://doi.org/10.1101/2022.01.14.476404
History 
  • January 17, 2022.

Article Versions

  • You are currently viewing Version 1 of this article (January 17, 2022 - 08:42).
  • Version 2 (January 21, 2022 - 09:48).
  • View Version 3, the most recent version of this article.
Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.

Author Information

  1. Mitchell FennellA,*,
  2. Christopher BeirneA and
  3. A. Cole BurtonA
  1. ADepartment of Forest Resources Management, University of British Columbia, 2424 Main Mall, V5T 1Z4, Vancouver, BC, Canada
  1. ↵*Corresponding Author: mitchell.fennell{at}gmail.com
Back to top
PreviousNext
Posted January 17, 2022.
Download PDF
Data/Code
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Use of object detection in camera trap image identification: assessing a method to rapidly and accurately classify human and animal detections for research and application in recreation ecology
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Use of object detection in camera trap image identification: assessing a method to rapidly and accurately classify human and animal detections for research and application in recreation ecology
Mitchell Fennell, Christopher Beirne, A. Cole Burton
bioRxiv 2022.01.14.476404; doi: https://doi.org/10.1101/2022.01.14.476404
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Use of object detection in camera trap image identification: assessing a method to rapidly and accurately classify human and animal detections for research and application in recreation ecology
Mitchell Fennell, Christopher Beirne, A. Cole Burton
bioRxiv 2022.01.14.476404; doi: https://doi.org/10.1101/2022.01.14.476404

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Ecology
Subject Areas
All Articles
  • Animal Behavior and Cognition (3607)
  • Biochemistry (7581)
  • Bioengineering (5529)
  • Bioinformatics (20809)
  • Biophysics (10338)
  • Cancer Biology (7988)
  • Cell Biology (11647)
  • Clinical Trials (138)
  • Developmental Biology (6611)
  • Ecology (10217)
  • Epidemiology (2065)
  • Evolutionary Biology (13630)
  • Genetics (9550)
  • Genomics (12854)
  • Immunology (7925)
  • Microbiology (19555)
  • Molecular Biology (7668)
  • Neuroscience (42147)
  • Paleontology (308)
  • Pathology (1258)
  • Pharmacology and Toxicology (2203)
  • Physiology (3269)
  • Plant Biology (7051)
  • Scientific Communication and Education (1294)
  • Synthetic Biology (1952)
  • Systems Biology (5429)
  • Zoology (1119)