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  Predicting landscapes from environmental conditions using generative networks

Requena-Mesa, C., Reichstein, M., Mahecha, M. D., Kraft, B., & Denzler, J. (2019). Predicting landscapes from environmental conditions using generative networks. In G. A. FInk, S. Frintrop, & X. Jiang (Eds.), Pattern Recognition, DAGM GCPR 2019 (pp. 203-217). Cham: Springer. doi:10.1007/978-3-030-33676-9_14.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0005-B21D-2 Version Permalink: https://hdl.handle.net/21.11116/0000-000A-3FA6-5
Genre: Book Chapter

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BGC3259s1.pdf (Supplementary material), 3MB
 
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 Creators:
Requena-Mesa, Christian1, 2, Author           
Reichstein, Markus3, Author           
Mahecha, Miguel D.1, Author           
Kraft, Basil2, 4, Author           
Denzler, Joachim, Author
Affiliations:
1Empirical Inference of the Earth System, Dr. Miguel D. Mahecha, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1938312              
2IMPRS International Max Planck Research School for Global Biogeochemical Cycles, Max Planck Institute for Biogeochemistry, Max Planck Society, Hans-Knöll-Str. 10, 07745 Jena, DE, ou_1497757              
3Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1688139              
4Global Diagnostic Modelling, Dr. Martin Jung, Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1938311              

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 Dates: 20192019-10-252019
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: Other: BGC3259
DOI: 10.1007/978-3-030-33676-9_14
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Title: Pattern Recognition, DAGM GCPR 2019
Source Genre: Book
 Creator(s):
FInk, G. A.1, Editor
Frintrop, S., Editor
Jiang, X., Editor
Affiliations:
1 41st DAGM German Conference, DAGM GCPR 2019 Dortmund, Germany, September 10–13, 2019, Proceedings, ou_persistent22            
Publ. Info: Cham : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 203 - 217 Identifier: ISBN: 978-3-030-33676-9

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Title: Lecture Notes in Computer Science
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Pages: - Volume / Issue: 11824 Sequence Number: - Start / End Page: 203 - 217 Identifier: -