Intelligent Radiation: A review of Machine learning applications in nuclear and radiological sciences

Author:

Jinia Abbas J.,Clarke Shaun D.,Moran Jean M.,Pozzi Sara A.

Funder

National Nuclear Security Administration

National Institutes of Health

US Department of Energy

National Cancer Institute

Publisher

Elsevier BV

Reference95 articles.

1. Semi-Supervised Gaussian Mixture Variational Autoencoder for Pulse Shape Discrimination, in;Abdulaziz,2022

2. The application of artificial neural network in material identification by multi-energy photon attenuation technique;Ahmadabadi;Nucl Instrum Methods Phys Res A,2023

3. Aleksandra Peeva, 2021. Pioneering IAEA Meeting to Focus on AI-Based Approaches in Nuclear Technologies. IAEA Department of Nuclear Sciences and Applications. URL https://www.iaea.org/newscenter/news/pioneering-iaea-meeting-to-focus-on-ai-based-approaches-in-nuclear-technologies (accessed 7.31.23).

4. Artificial neural network models for volatile fission product release during severe accident conditions;Andrews;Journal of Nuclear Materials,1999

5. Deep learning-guided estimation of attenuation correction factors from time-of-flight PET emission data;Arabi;Med Image Anal,2020

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