Towards an automated data cleaning with deep learning in CRESST.
Angloher G, Banik S, Bartolot D, Benato G, Bento A, Bertolini A, Breier R, Bucci C, Burkhart J, Canonica L, D'Addabbo A, Di Lorenzo S, Einfalt L, Erb A, Feilitzsch FV, Iachellini NF, Fichtinger S, Fuchs D, Fuss A, Garai A, Ghete VM, Gerster S, Gorla P, Guillaumon PV, Gupta S, Hauff D, Ješkovský M, Jochum J, Kaznacheeva M, Kinast A, Kluck H, Kraus H, Lackner M, Langenkämper A, Mancuso M, Marini L, Meyer L, Mokina V, Nilima A, Olmi M, Ortmann T, Pagliarone C, Pattavina L, Petricca F, Potzel W, Povinec P, Pröbst F, Pucci F, Reindl F, Rizvanovic D, Rothe J, Schäffner K, Schieck J, Schmiedmayer D, Schönert S, Schwertner C, Stahlberg M, Stodolsky L, Strandhagen C, Strauss R, Usherov I, Wagner F, Willers M, Zema V, Waltenberger W; CRESST Collaboration.
Angloher G, et al. Among authors: gerster s.
Eur Phys J Plus. 2023;138(1):100. doi: 10.1140/epjp/s13360-023-03674-2. Epub 2023 Jan 30.
Eur Phys J Plus. 2023.
PMID: 36741916
Free PMC article.
