A comparison of deep learning and citizen science techniques for counting wildlife in aerial survey images-Reference-Cited by-同舟云学术

A comparison of deep learning and citizen science techniques for counting wildlife in aerial survey images

Published:2019-03-05 Issue:6 Volume:10 Page:779-787
ISSN:2041-210X
Container-title:Methods in Ecology and Evolution
language:en
Short-container-title:Methods Ecol Evol

Author:

Torney Colin J.¹^ORCID,Lloyd‐Jones David J.²,Chevallier Mark¹,Moyer David C.³,Maliti Honori T.⁴,Mwita Machoke⁴,Kohi Edward M.⁴,Hopcraft Grant C.⁵

Affiliation:

1. School of Mathematics and StatisticsUniversity of Glasgow Glasgow UK

2. FitzPatrick Institute of African OrnithologyDST‐NRF Centre of ExcellenceUniversity of Cape Town Rondebosch South Africa

3. Integrated Research CenterThe Field Museum of Natural History Chicago Illinois

4. Tanzania Wildlife Research Institute Arusha Tanzania

5. Institute of Biodiversity, Animal Health and Comparative MedicineUniversity of Glasgow Glasgow UK

Funder

Horizon 2020 Framework Programme

James S. McDonnell Foundation

Publisher

Wiley

Subject

Ecological Modelling,Ecology, Evolution, Behavior and Systematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.13165

Reference61 articles.

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