Improved detection of highly energetic materials traces on surfaces by standoff laser-induced thermal emission incorporating neural networks

@inproceedings{FigueroaNavedo2013ImprovedDO,
  title={Improved detection of highly energetic materials traces on surfaces by standoff laser-induced thermal emission incorporating neural networks},
  author={Amanda M. Figueroa-Navedo and Nataly Y. Gal{\'a}n-Freyle and Leonardo C Pacheco-Londo{\~n}o and Samuel P. Hern{\'a}ndez-Rivera},
  booktitle={Defense, Security, and Sensing},
  year={2013}
}
  • Amanda M. Figueroa-Navedo, Nataly Y. Galán-Freyle, +1 author Samuel P. Hernández-Rivera
  • Published in
    Defense, Security, and…
    2013
  • Physics, Engineering
  • Terrorists conceal highly energetic materials (HEM) as Improvised Explosive Devices (IED) in various types of materials such as PVC, wood, Teflon, aluminum, acrylic, carton and rubber to disguise them from detection equipment used by military and security agency personnel. Infrared emissions (IREs) of substrates, with and without HEM, were measured to generate models for detection and discrimination. Multivariable analysis techniques such as principal component analysis (PCA), soft independent… CONTINUE READING

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