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  Beyond Measurement: Extracting Vegetation Height from High Resolution Imagery with Deep Learning

Radke, D., Radke, D., & Radke, J. (2020). Beyond Measurement: Extracting Vegetation Height from High Resolution Imagery with Deep Learning. Remote Sensing, 12(22): 3797. doi:10.3390/rs12223797.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0007-9A68-7 Version Permalink: https://hdl.handle.net/21.11116/0000-0007-9A70-D
Genre: Journal Article
Latex : Beyond Measurement: {E}xtracting Vegetation Height from High Resolution Imagery with Deep Learning

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c 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
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http://creativecommons.org/licenses/by/4.0/

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 Creators:
Radke, David1, Author
Radke, Daniel2, Author           
Radke, John1, Author
Affiliations:
1External Organizations, ou_persistent22              
2International Max Planck Research School, MPI for Informatics, Max Planck Society, ou_1116551              

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Language(s): eng - English
 Dates: 2020
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Radke2020
DOI: 10.3390/rs12223797
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Title: Remote Sensing
Source Genre: Journal
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Publ. Info: Basel : Molecular Diversity Preservation International (MDPI)
Pages: - Volume / Issue: 12 (22) Sequence Number: 3797 Start / End Page: - Identifier: ISSN: 2072-4292
CoNE: https://pure.mpg.de/cone/journals/resource/2072-4292