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  Image-based automated recognition of 31 Poaceae species: The most relevant perspectives

Rzanny, M., Wittich, H. C., Mäder, P., Deggelmann, A., Boho, D., & Wäldchen, J. (2022). Image-based automated recognition of 31 Poaceae species: The most relevant perspectives. Frontiers in Plant Science, 12: 804140. doi:10.3389/fpls.2021.804140.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0009-E34D-1 Version Permalink: https://hdl.handle.net/21.11116/0000-000A-006C-D
Genre: Journal Article

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https://doi.org/10.3389/fpls.2021.804140 (Publisher version)
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 Creators:
Rzanny, Michael1, Author           
Wittich, Hans Christian, Author
Mäder, Patrick, Author
Deggelmann, Alice1, Author           
Boho, David, Author
Wäldchen, Jana1, Author           
Affiliations:
1Flora Incognita, Dr. Jana Wäldchen, Department Biogeochemical Integration, Prof. Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_3240484              

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 Dates: 2021-12-202022-01-26
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: Other: BGC3807
DOI: 10.3389/fpls.2021.804140
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Title: Frontiers in Plant Science
  Abbreviation : Front. Plant Sci.
Source Genre: Journal
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Publ. Info: Lausanne : Frontiers Media
Pages: - Volume / Issue: 12 Sequence Number: 804140 Start / End Page: - Identifier: ISSN: 1664-462X
CoNE: https://pure.mpg.de/cone/journals/resource/1664462X