Automated Isotope Identification and Quantification Using Artificial Neural Networks
Dataset Description |
This dataset contains gamma-ray spectra templates for a source interdiction and uranium enrichment measurement task. This dataset also contains Keras machine learning models trained using datasets created using these templates. |
Subject |
Physical Sciences |
Keywords |
gamma-ray spectroscopy; neural networks; machine learning; isotope identification; uranium enrichment; sodium iodide; NaI(Tl) |
License |
CC BY |
Funder |
U.S. Department of Energy (DOE)-Grant:DE-NA0002534 |
Corresponding Creator |
Kathryn Huff |
Downloaded |
5958 times |
| Version | DOI | Comment | Publication Date |
|---|---|---|---|
| 1 | 10.13012/B2IDB-4860767_V1 | 2019-12-12 |
Contact the Research Data Service for help interpreting this log.
| RelatedMaterial | destroy: {"material_type"=>"Code", "availability"=>nil, "link"=>"https://github.com/arfc/annsa", "uri"=>"", "uri_type"=>"", "citation"=>"", "dataset_id"=>1159, "selected_type"=>"Code", "datacite_list"=>"", "note"=>nil, "feature"=>nil} | 2025-01-08T23:48:40Z |