A comparison of machine learning methods to classify radioactive elements using prompt-gamma-ray neutron activation data
Abstract The detection of illicit radiological materials is critical to establishing a robust second line of defence in nuclear security. Neutron-capture prompt-gamma activation analysis (PGAA) can be used to detect multiple radioactive materials across the entire Periodic Table. However, long detec...
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| Hlavní autoři: | , , , , , , , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
Nature Portfolio
2023-06-01
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| Edice: | Scientific Reports |
| On-line přístup: | https://doi.org/10.1038/s41598-023-36832-8 |
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