Deep learning-based spectrum-dose prediction for a plastic scintillation detector-Reference-Cited by-同舟云学术

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Deep learning-based spectrum-dose prediction for a plastic scintillation detector

Published:2022-11 Issue: Volume:201 Page:110444
ISSN:0969-806X
Container-title:Radiation Physics and Chemistry
language:en
Short-container-title:Radiation Physics and Chemistry

Author:

Hwang Jisung,Jeon Byoungil,Kim Junhyeok,Kim Hyoungtaek,Cho Gyuseong

Funder

Korea Atomic Energy Research Institute

National Research Foundation of Korea

Institute for Information and Communications Technology Promotion

Ministry of Science, ICT and Future Planning

Publisher

Elsevier BV

Subject

Radiation

Reference60 articles.

1. TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems;Abadi,2016

2. Comprehensive review of artificial neural network applications to pattern recognition;Abiodun;IEEE Access,2019

3. A comparative analysis of 9 multi-model averaging approaches in hydrological continuous streamflow simulation;Arsenault;J. Hydrol.,2015

4. Review of plastic and liquid scintillation dosimetry for photon, electron, and proton therapy;Beaulieu;Phys. Med. Biol.,2016

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2. A counting-time optimization method for artificial neural network (ANN) based gamma-ray spectroscopy;Nuclear Engineering and Technology;2024-07

3. Deep Learning-Based Method for Activity Estimation From Short-Duration Gamma Spectroscopy Recordings;IEEE Transactions on Instrumentation and Measurement;2024

4. Estimation of ambient dose equivalent rate with a plastic scintillation detector using the least-square and first-order methods-based G(E) function;Applied Radiation and Isotopes;2023-04

5. Optical and Scintillation Properties of Tb-Doped Rare-Earth Pyrosilicate Single Crystals;Photonics;2022-10-13

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