The Supervised Normalized Cut Method for Detecting, Classifying, and Identifying Special Nuclear Materials

The detection of illicit nuclear materials is a major tool in preventing and deterring nuclear terrorism. The detection task is extremely difficult because of physical limitations of nuclear radiation detectors, shielding by intervening cargo materials, and the presence of background noise. We aim a...

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Veröffentlicht in:	INFORMS journal on computing 2014-01, Vol.26 (1), p.45-58
Hauptverfasser:	Yang, Yan T, Fishbain, Barak, Hochbaum, Dorit S, Norman, Eric B, Swanberg, Erik
Format:	Artikel
Sprache:	eng
Schlagworte:	Algebra Analysis Classification Computational mathematics Cooling Data mining Datasets Detectors Discriminant analysis Gamma rays Graph theory Machine learning Methods multiclassification normalized cut Nuclear energy nuclear material detection Nuclear radiation Plutonium Principal components analysis Questioning Radiation detectors Radioactive substances Studies supervised learning support vector machine Support vector machines Uranium
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