Surveying wildlife and livestock in Uganda with aerial cameras: Deep Learning reduces the workload of human interpretation by over 70%

Surveying wildlife and livestock in Uganda with aerial cameras: Deep Learning reduces the workload of human interpretation by over 70%

As the need to accurately monitor key-species populations grows amid increasing pressures on global biodiversity, the counting of large mammals in savannas has traditionally relied on the Systematic-Reconnaissance-Flight (SRF) technique using light aircrafts and human observers. However, this method...

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Bibliographic Details
Main Authors: Alexandre Delplanque, Richard Lamprey, Samuel Foucher, Jérôme Théau, Philippe Lejeune
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-11-01
Series:Frontiers in Ecology and Evolution
Subjects:
wildlife
aerial survey
Deep Learning
remote sensing
convolutional neural networks
animal conservation
Online Access:https://www.frontiersin.org/articles/10.3389/fevo.2023.1270857/full

Internet

https://www.frontiersin.org/articles/10.3389/fevo.2023.1270857/full

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