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Extracting low energy signals from raw LArTPC waveforms using deep learning techniques — A proof of concept
We investigate the feasibility of using deep learning techniques, in the form of a one-dimensional convolutional neural network (1D-CNN), for the extraction of signals from the raw waveforms produced by the individual channels of liquid argon time projection chamber (LArTPC) detectors. A minimal gen...
| Autores principales: | , , , , , , |
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| Lenguaje: | eng |
| Publicado: |
2021
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1016/j.nima.2022.166371 http://cds.cern.ch/record/2773634 |