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0550827 - FZÚ 2022 RIV GB eng J - Journal Article
Aab, A. - Abreu, P. - Aglietta, M. - Bakalová, Alena - Blažek, Jiří - Boháčová, Martina - Chudoba, Jiří - Ebr, Jan - Hamal, Petr - Janeček, Petr - Juryšek, Jakub - Mandát, Dušan - Palatka, Miroslav - Pech, Miroslav - Prouza, Michael - Řídký, Jan - dos Santos, Eva M. Martins - Schovánek, Petr - Tobiška, Petr - Trávníček, Petr - Vícha, Jakub - Yushkov, Alexey … Total 372 authors
Deep-learning based reconstruction of the shower maximum X_max using the water-Cherenkov detectors of the Pierre Auger Observatory.
Journal of Instrumentation. Roč. 16, č. 7 (2021), č. článku P07019. ISSN 1748-0221. E-ISSN 1748-0221
R&D Projects: GA MŠMT LTT18004; GA MŠMT(CZ) EF18_046/0016010; GA MŠMT EF16_013/0001402; GA MŠMT LM2015038
Grant - others:OP VVV - AUGERII.CZ(XE) CZ.02.1.01/0.0/0.0/18_046/0016010; OP VVV - AUGER-CZ(XE) CZ.02.1.01/0.0/0.0/16_013/0001402
Research Infrastructure: AUGER-CZ II - 90102
Institutional support: RVO:68378271
Keywords : data analysis * pattern recognition * cluster finding * calibration and fitting methods * large detector systems for particle and astroparticle physics * particle identification methods
OECD category: Particles and field physics
Impact factor: 1.121, year: 2021
Method of publishing: Open access
Permanent Link: http://hdl.handle.net/11104/0326140