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- W4379196961 abstract "We developed a multi-tasking deep learning model for simultaneous pulse height estimation and pulse shape discrimination for pile-up n/γ signals. Compared with single-tasking models, our model showed better spectral correction performance with higher recall for neutrons. Further, it achieved more stable neutron counting with less signal loss and a lower error rate in the predicted gamma ray spectra. Our model can be applied to a dual radiation scintillation detector to discriminatively reconstruct each radiation spectrum for radioisotope identification and quantitative analysis." @default.
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- W4379196961 date "2023-09-01" @default.
- W4379196961 modified "2023-09-26" @default.
- W4379196961 title "Pulse height estimation and pulse shape discrimination in pile-up neutron and gamma ray signals from an organic scintillation detector using multi-task learning" @default.
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- W4379196961 doi "https://doi.org/10.1016/j.apradiso.2023.110880" @default.
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