Machine learning-assisted techniques for Compton-background discrimination in Broad Energy Germanium...
Machine learning-assisted techniques for Compton-background discrimination in Broad Energy Germanium (BEGe) detector
About this item
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Author / Creator
Baccolo, G. , Barresi, A. , Chiesa, D. , Giachero, A. , Labranca, D. , Moretti, R. , Nastasi, M. , Paonessa, A. , Picione, M. , Previtali, E. and Sisti, M.
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title
Language
English
Formats
Publication information
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Subjects
More information
Scope and Contents
Contents
High Purity Germanium (HPGe) detectors are powerful detectors for gamma-ray spectroscopy. The sensitivity to low-intensity gamma-ray peaks is often hindered by the presence of Compton continuum distributions, originated by gamma-rays emitted at higher energies. This study explores novel, pulse shape-based, machine learning-assisted techniques to en...
Alternative Titles
Full title
Machine learning-assisted techniques for Compton-background discrimination in Broad Energy Germanium (BEGe) detector
Authors, Artists and Contributors
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Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_eb4b55948f7545ee963652a99668cc16
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_eb4b55948f7545ee963652a99668cc16
Other Identifiers
ISSN
1434-6052,1434-6044
E-ISSN
1434-6052
DOI
10.1140/epjc/s10052-025-14042-y
