Machine learning to detect marine animals in UAV imagery: effect of morphology, spacing, behaviour and habitat

Machine learning to detect marine animals in UAV imagery: effect of morphology, spacing, behaviour and habitat

Abstract Machine learning algorithms are being increasingly used to process large volumes of wildlife imagery data from unmanned aerial vehicles (UAVs); however, suitable algorithms to monitor multiple species are required to enhance efficiency. Here, we developed a machine learning algorithm using...

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Bibliographic Details
Main Authors: Antoine M. Dujon, Daniel Ierodiaconou, Johanna J. Geeson, John P. Y. Arnould, Blake M. Allan, Kostas A. Katselidis, Gail Schofield
Format: Article
Language:English
Published: Wiley 2021-09-01
Series:Remote Sensing in Ecology and Conservation
Subjects:
aerial surveys
demography
satellite imagery
deep learning
artificial intelligence
movement ecology
Online Access:https://doi.org/10.1002/rse2.205

Internet

https://doi.org/10.1002/rse2.205

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