Deep Neural Networks for Particle Identification with Si Detectors through traces

This repository consists of the code used for the creation, training and analysis of neural networks for particle identification with Silicon detectors. In addition also consists of the code used for the analysis of CsI deposited on mylar for evaluation of efficiency and electron production for MCP detectors

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-28
DOI
https://doi.org/10.5281/zenodo.16986731
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

Deep Neural Networks for Particle Identification with Si Detectors through traces

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

Deep Neural Networks for Particle Identification with Si Detectors through traces

article en

Abstract

This repository consists of the code used for the creation, training and analysis of neural networks for particle identification with Silicon detectors. In addition also consists of the code used for the analysis of CsI deposited on mylar for evaluation of efficiency and electron production for MCP detectors

Zenodo (CERN European Organization for Nuclear Research)
University of Padua (IT), Istituto Nazionale di Fisica Nucleare (IT), Istituto Nazionale di Fisica Nucleare, Laboratori Nazionali di Legnaro (IT)
Openalex Percentile: Top 63%
Geochemistry and Geologic Mapping
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