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Development of Neural Network Model With Explainable AI for Measuring Uranium Enrichment

  • Published:2021-11 Issue:11 Volume:68 Page:2670-2681
  • ISSN:0018-9499
  • Container-title:IEEE Transactions on Nuclear Science
  • language:
  • Short-container-title:IEEE Trans. Nucl. Sci.

Author:

Ryu JichangORCID,Park Chanjun,Park Jungsuk,Cho Namchan,Park Jaehyun,Cho Gyuseong

Funder

KEPCO Nuclear Fuel Company Ltd

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Nuclear Energy and Engineering,Nuclear and High Energy Physics

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine learning framework for predicting uranium enrichments from M400 CZT gamma spectra;Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment;2024-11

2. Integrating Tagged Neutron Inspection with Explainable AI for Threat Material Identification;2024-07-24

3. Machine Learning technique for isotopic determination of radioisotopes using HPGe γ-ray spectra;Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment;2023-09

4. Explaining machine-learning models for gamma-ray detection and identification;PLOS ONE;2023-06-20

5. Explainable Artificial Intelligence (XAI) for Intrusion Detection and Mitigation in Intelligent Connected Vehicles: A Review;Applied Sciences;2023-01-17
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