21 000 birds in 4.5 h: efficient large‐scale seabird detection with machine learning

21 000 birds in 4.5 h: efficient large‐scale seabird detection with machine learning

Abstract We address the task of automatically detecting and counting seabirds in unmanned aerial vehicle (UAV) imagery using deep convolutional neural networks (CNNs). Our study area, the coast of West Africa, harbours significant breeding colonies of terns and gulls, which as top predators in the f...

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Bibliographic Details
Main Authors: Benjamin Kellenberger, Thor Veen, Eelke Folmer, Devis Tuia
Format: Article
Language:English
Published: Wiley 2021-09-01
Series:Remote Sensing in Ecology and Conservation
Subjects:
coastal birds
convolutional neural network
deep learning
remote sensing
unmanned aerial vehicle
wildlife census
Online Access:https://doi.org/10.1002/rse2.200

Internet

https://doi.org/10.1002/rse2.200

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