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Title:Air-Shower Reconstruction at the Pierre Auger Observatory based on Deep Learning
Authors:ID Glombitza, Jonas (Author)
ID Filipčič, Andrej (Author)
ID Kukec Mezek, Gašper (Author)
ID Stanič, Samo (Author)
ID Trini, Marta (Author)
ID Vorobiov, Serguei (Author)
ID Yang, Lili (Author)
ID Zavrtanik, Danilo (Author)
ID Zavrtanik, Marko (Author)
ID Zehrer, Lukas (Author), et al.
Files:.pdf ICRC2019_270.pdf (1,16 MB)
MD5: A97D7EF6BC31DAC36D1154635AE5C278
 
Language:English
Work type:Not categorized
Typology:1.08 - Published Scientific Conference Contribution
Organization:UNG - University of Nova Gorica
Keywords:Pierre Auger Observatory, extensive air showers, event reconstruction, deep learning
Publication status:Published
Year of publishing:2019
PID:20.500.12556/RUNG-5576-d8ca9dd5-36eb-2b24-840b-a55df0dcdb9f New window
COBISS.SI-ID:19734787 New window
NUK URN:URN:SI:UNG:REP:QZCLFCKE
Publication date in RUNG:16.06.2020
Views:2867
Downloads:80
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Record is a part of a monograph

Title:Proceedings of the 36th International Cosmic Ray Conference : ICRC2019
Place of publishing:SISSA, Italy
Year of publishing:2019

Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:16.06.2020

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