Predicting animal behaviour using deep learning: GPS data alone accurately predict diving in seabirds-Reference-Cited by-同舟云学术

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Predicting animal behaviour using deep learning: GPS data alone accurately predict diving in seabirds

Published:2017-11-20 Issue:3 Volume:9 Page:681-692
ISSN:2041-210X
Container-title:Methods in Ecology and Evolution
language:en
Short-container-title:Methods Ecol Evol

Author:

Browning Ella¹²^ORCID,Bolton Mark³,Owen Ellie⁴,Shoji Akiko⁵,Guilford Tim⁵,Freeman Robin²

Affiliation:

1. Centre for Biodiversity and Environment ResearchUniversity College London London UK

2. Institute of ZoologyZoological Society of London London UK

3. RSPB Centre for Conservation Science Sandy Bedfordshire UK

4. RSPB Centre for Conservation Science Inverness UK

5. Department of ZoologyOxford University Oxford UK

Funder

Natural Environment Research Council

Publisher

Wiley

Subject

Ecological Modeling,Ecology, Evolution, Behavior and Systematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.12926

Reference55 articles.

1. Aiello S. Kraljevic T. &Maj P. (2015).R Interface for H2O. R package version 3.0.0.22.www.h2o.ai

2. How to reliably estimate the tortuosity of an animal's path:

3. Tracking apex marine predator movements in a dynamic ocean

4. State-space methods for more completely capturing behavioral dynamics from animal tracks

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