imageseg: An R package for deep learning‐based image segmentation-Reference-Cited by-同舟云学术

imageseg: An R package for deep learning‐based image segmentation

Published:2022-10-02 Issue:11 Volume:13 Page:2363-2371
ISSN:2041-210X
Container-title:Methods in Ecology and Evolution
language:en
Short-container-title:Methods Ecol Evol

Author:

Niedballa Jürgen¹^ORCID,Axtner Jan¹^ORCID,Döbert Timm Fabian²^ORCID,Tilker Andrew¹³^ORCID,Nguyen An¹^ORCID,Wong Seth T.¹^ORCID,Fiderer Christian⁴⁵^ORCID,Heurich Marco⁴⁵⁶^ORCID,Wilting Andreas¹^ORCID

Affiliation:

1. Department of Ecological Dynamics Leibniz Institute for Zoo and Wildlife Research Berlin Germany

2. Department of Earth and Atmospheric Sciences University of Alberta Edmonton Alberta Canada

3. Re:wild Austin Texas USA

4. Bavarian Forest National Park Grafenau Germany

5. Albert‐Ludwigs Universität Freiburg Freiburg Germany

6. Inland Norway University of Applied Science Koppang Norway

Funder

Bundesamt für Naturschutz

Bundesministerium für Bildung und Forschung

Commonwealth Scientific and Industrial Research Organisation

Deutsche Forschungsgemeinschaft

United States Agency for International Development

University of Western Australia

Publisher

Wiley

Subject

Ecological Modeling,Ecology, Evolution, Behavior and Systematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.13984

Reference43 articles.

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4. Reduction in browsing intensity may not compensate climate change effects on tree species composition in the Bavarian Forest National Park

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