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    0563954 - FZÚ 2023 RIV DE eng J - Journal Article
    Abed Abud, A. - Abi, B. - Acciarri, R. - Filip, Peter - Kvasnička, Jiří - Lokajíček, Miloš - Pěč, Viktor - Zálešák, Jaroslav - Zuklín, Josef … Total 1228 authors
    Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network.
    European Physical Journal C. Roč. 82, č. 10 (2022), č. článku 903. ISSN 1434-6044. E-ISSN 1434-6052
    Research Infrastructure: Fermilab-CZ II - 90113
    Institutional support: RVO:68378271
    Keywords : DUNE * neural network * efficiency * performance
    OECD category: Particles and field physics
    Impact factor: 4.4, year: 2022
    Method of publishing: Open access
    Permanent Link: https://hdl.handle.net/11104/0335738
    FileDownloadSizeCommentaryVersionAccess
    0563954.pdf03.3 MBCC LicencePublisher’s postprintopen-access
     
     

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