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Atmospheric Tomography Using Convolutional Neural Networks

Author:
González Gutiérrez, CarlosUniovi authority; Beltramo Martin, O.; Osborn, J.; Calvo Rolle, José Luis; Cos Juez, Francisco Javier deUniovi authority
Publication date:
2020
Publisher version:
http://dx.doi.org/10.1007/978-3-030-62365-4_54
Serie:

Lecture Notes in Computer Science; 12490

Descripción física:
p. 561-569
Description:

International Conference Intelligent Data Engineering and Automated Learning – IDEAL (21st. 2020. Guimaraes, Portugal)

URI:
http://hdl.handle.net/10651/58654
ISBN:
9783030623647
ISSN:
0302-9743
DOI:
10.1007/978-3-030-62365-4_54
Patrocinado por:

The authors acknowledge Spanish ministry projects MINECO AYA2017-89121- P, and support from the European Union’s Horizon 2020 research and innovation program under the H2020-INFRAIA-2018-2020 grant agreement No 210489629. This work has been partially funded by the French National Research Agency (ANR) program APPLY - ANR-19-CE31-0011. This work also benefited from the support of the WOLF project ANR-18-CE31-0018 of the and the OPTICON H2020 (2017–2020) Work Package 1. James Osborn acknowledges support from the UKRI Future Leaders Fellowship (UK) (MR/S035338/1).

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