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  Generative adversarial networks in the Geosciences

Mateo-García, G., Laparra, V., Requena Mesa, C., & Gómez-Chova, L. (2021). Generative adversarial networks in the Geosciences. In G. Camps-Valls, D. Tuia, X. X. Zhu, & M. Reichstein (Eds.), Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote Sensing, Climate Science, and Geosciences (pp. 24-36). Hoboken, New Jersey: John Wiley & Sons Ltd.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0009-94CB-B Version Permalink: https://hdl.handle.net/21.11116/0000-0009-9AEF-D
Genre: Book Chapter

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 Creators:
Mateo-García, Gonzalo, Author
Laparra, Valero, Author
Requena Mesa, Christian1, 2, Author           
Gómez-Chova, Luis, Author
Affiliations:
1Empirical Inference of the Earth System, Dr. Miguel D. Mahecha, Department Biogeochemical Integration, Prof. 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              

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 Dates: 2021-08-20
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: Other: BGC3774
DOI: 10.1002/9781119646181.ch3
 Degree: -

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Title: Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote Sensing, Climate Science, and Geosciences
Source Genre: Book
 Creator(s):
Camps-Valls, Gustau1, Editor
Tuia, Devis, Editor
Zhu, Xiao Xiang, Editor
Reichstein, Markus1, Editor           
Affiliations:
1 Department Biogeochemical Integration, Prof. Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1688139            
Publ. Info: Hoboken, New Jersey : John Wiley & Sons Ltd
Pages: 405 Volume / Issue: - Sequence Number: - Start / End Page: 24 - 36 Identifier: ISBN: 9781119646143