Influence of Machine Learning and Gamma-Ray Spectral Parameters on Novelty Detection and Novelty Localization-Reference-Cited by-同舟云学术

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Influence of Machine Learning and Gamma-Ray Spectral Parameters on Novelty Detection and Novelty Localization

Published:2022-11-05 Issue: Volume:66 Page:1-4
ISSN:
Container-title:2022 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)
language:
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Author:

Fjeldsted Aaron P.¹,Holland Darren E.²,Landon George V.³,Scott Clayton D.⁴,Zhu Yilun⁴,Lintereur Azaree T.¹

Affiliation:

1. Penn State University,Ken and Mary Alice Lindquist Department of Nuclear Engineering

2. Air Force Institute of Technology,Department of Engineering Physics

3. Cedarville University,School of Engineering and Computer Science

4. University of Michigan,Department of Electrical Engineering and Computer Science

Funder

Defense Threat Reduction Agency

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10398888/10398889/10399059.pdf?arnumber=10399059

Reference12 articles.

1. Anomaly detection in gamma ray spectra: A machine learning perspective

2. A Datacentric Algorithm for Gamma-ray Radiation Anomaly A Datacentric Algorithm for Gamma-ray Radiation Anomaly Detection in Unknown Background Environments Detection in Unknown Background Environments;Ghawaly,2020

3. Statistical analysis of uncertainties of gamma-peak identification;Zhang;Applied Radiation and Isotopes,2008

4. Analysis of spectroscopic radiation portal monitor data using principal components analysis

5. Examination of Count-starved Gamma Spectra Using the Method of Spectral Comparison Ratios

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