Efficacy of automated detection of motion in wildlife monitoring videos-Reference-Cited by-同舟云学术

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Efficacy of automated detection of motion in wildlife monitoring videos

Published:2019-10-20 Issue:4 Volume:43 Page:726-736
ISSN:1938-5463
Container-title:Wildlife Society Bulletin
language:en
Short-container-title:Wildl. Soc. Bull.

Author:

Marcot Bruce G.¹,Lorenz Teresa J.²,Fischer Philip³,Weinstein Ben G.⁴,Cowell Samuel⁵

Affiliation:

1. U.S. Forest Service, Pacific Northwest Research Station 620 SW Main Street Portland OR 97205 USA

2. U.S. Forest Service, Pacific Northwest Research Station 3625 93rd Avenue SW Olympia WA 98512 USA

3. 27291 US Highway 12 Naches WA 98937 USA

4. Department of Fisheries and Wildlife, Marine Mammal InstituteOregon State University 2030 Marine Science Drive Newport OR 97365 USA

5. Department of BiologyUtah State University 5305 Old Main Hill Logan UT 84322 USA

Publisher

Wiley

Subject

Nature and Landscape Conservation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/wsb.1016

Reference43 articles.

1. The Comparative Effects of Large Carnivores on the Acquisition of Carrion by Scavengers

2. Computer Vision Syndrome: A Review

3. Remote monitoring of nests using digital camera technology

4. Analysing animal behaviour in wildlife videos using face detection and tracking

5. Camera traps in the canopy: surveying wildlife at tree hollow entrances

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Comparison of manual, machine learning, and hybrid methods for video annotation to extract parental care data;Journal of Avian Biology;2023-12-14

2. Seeing wildlife behavior in a new way: Novel utilization of computer vision for focal reptile videography behavior study;Wildlife Society Bulletin;2023-02-21

3. Towards the fully automated monitoring of ecological communities;Ecology Letters;2022-10-20

4. Livestock Management With Unmanned Aerial Vehicles: A Review;IEEE Access;2022

5. An intelligent and cost-effective remote underwater video device for fish size monitoring;Ecological Informatics;2021-07

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