21 000 birds in 4.5 h: efficient large‐scale seabird detection with machine learning-Reference-Cited by-同舟云学术

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

Published:2021-03-25 Issue:3 Volume:7 Page:445-460
ISSN:2056-3485
Container-title:Remote Sensing in Ecology and Conservation
language:en
Short-container-title:Remote Sens Ecol Conserv

Author:

Kellenberger Benjamin¹²^ORCID,Veen Thor³⁴,Folmer Eelke⁴,Tuia Devis²^ORCID

Affiliation:

1. Laboratory of Geo‐Information Science and Remote Sensing Wageningen University & Research Wageningen The Netherlands

2. Environmental Computational Science and Earth Observation Laboratory (ECEO) EPFL Sion Switzerland

3. Quest University Squamish Canada

4. Aeria Solutions Ltd. Squamish Canada

Funder

Nvidia

Publisher

Wiley

Subject

Nature and Landscape Conservation,Computers in Earth Sciences,Ecology,Ecology, Evolution, Behavior and Systematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/rse2.200

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5. On the Statistical Analysis of Dirty Pictures

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