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DOE OSTI · 1601598

MAD using INRAD and Radiography [Slides]

Klasky, Marc Louis·Watkins, Yijing Z.·Skau, Erik West·Stults, Katrina Ann·Hung, Li-Wei
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Abstract

We have previously evaluated Intrinsic Radiation Detection Algorithms from vendors for the Department of Homeland Security. These algorithms have limited spectra capability due to both the relatively low spectral content of the signal due to the use of PVT in the Radiation Portal detectors as well as relatively simple algorithms which are based on energy windowing and other simple algorithms to perform classification of Special Nuclear Material. Current detection algorithms are suceptible to nuissance alarms due to Naturally Occuring Radiation (NORM) and variations in background suppression. In this work, we propose to fuse the intrinsic radiation and radiographic data in conjunction with well-established machine learning algorithms to developed enhanced Threat Object detection capability.

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45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEFENSE97 MATHEMATICS AND COMPUTING

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Klasky, Marc Louis, Watkins, Yijing Z., Skau, Erik West, Stults, Katrina Ann, Hung, Li-Wei. 2020-01-21. MAD using INRAD and Radiography [Slides]. https://doi.org/10.2172/1601598

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