Research output: Contribution to journal › Article › peer-review
What Machine Learning Can Do for Focusing Aerogel Detectors. / Shipilov, Foma; Barnyakov, Alexander; Bobrovnikov, Vladimir et al.
In: EPJ Web of Conferences, Vol. 295, 09043, 04.09.2024.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - What Machine Learning Can Do for Focusing Aerogel Detectors
AU - Shipilov, Foma
AU - Barnyakov, Alexander
AU - Bobrovnikov, Vladimir
AU - Kononov, Sergey
AU - Ratnikov, Fedor
N1 - Conference code: 26
PY - 2024/9/4
Y1 - 2024/9/4
N2 - Particle identification at the Super Charm-Tau factory experiment will be provided by a Focusing Aerogel Ring Imaging CHerenkov detector (FARICH). The specifics of detector location make proper cooling difficult, therefore a significant number of ambient background hits are captured. They must be mitigated to reduce the data flow and improve particle velocity resolution. In this work we present several approaches to filtering signal hits, inspired by machine learning techniques from computer vision.
AB - Particle identification at the Super Charm-Tau factory experiment will be provided by a Focusing Aerogel Ring Imaging CHerenkov detector (FARICH). The specifics of detector location make proper cooling difficult, therefore a significant number of ambient background hits are captured. They must be mitigated to reduce the data flow and improve particle velocity resolution. In this work we present several approaches to filtering signal hits, inspired by machine learning techniques from computer vision.
UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85212177025&origin=inward&txGid=2849bb1e7059d72233443d090e53458c
UR - https://www.webofscience.com/wos/woscc/full-record/WOS:001244151902094
UR - https://www.mendeley.com/catalogue/ab2c1bd5-a105-3fd3-bda0-bcd37277a689/
U2 - 10.1051/epjconf/202429509043
DO - 10.1051/epjconf/202429509043
M3 - Article
VL - 295
JO - EPJ Web of Conferences
JF - EPJ Web of Conferences
SN - 2101-6275
M1 - 09043
T2 - 26th International Conference on Computing in High Energy and Nuclear Physics
Y2 - 8 May 2023 through 12 May 2023
ER -
ID: 61237184