Journal Article

GSI-2026-00251

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Deep-Learning-Based Optimization of the Signal/Background Ratio for $\Lambda$ Particles in the CBM Experiment at FAIR

Kisel, I. (Corresponding author)GSI* ; Lakos, R. (Corresponding author) ; Zischka, G. (Corresponding author)

2025
MDPI Basel

Please use a persistent id in citations: doi:10.3390/a18040229  doi:10.15120/GSI-2026-00251

Note: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). This research was partly funded by the Federal Ministry of Education and Research [grant numbers 01IS21092, 05P24RF3, 05P24RF7]

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Contributing Institute(s):

1. Helmholtz ForschAkad Hess. f. FAIR, HFHF (FHF)

Research Program(s):

1. 623 - Data Management and Analysis (POF4-623) (POF4-623)
2. Scientific computing (HFHF project) (I:(DE-Ds200)HFHF-COMP) (I:(DE-Ds200)HFHF-COMP)

Experiment(s):

1. no experiment theory work (theory)

Appears in the scientific report 2025

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Database coverage:
; ; ; ; Article Processing Charges ; Clarivate Analytics Master Journal List ; DOAJ Seal ; Ebsco Academic Search ; Emerging Sources Citation Index ; Fees ; IF < 5 ; JCR ; SCOPUS ; Web of Science Core Collection

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