Abstract
Various pattern-recognition techniques have been examined to evaluate their usefulness in automated detection and identification of explosives that constitute a threat when used in bombs in public place or airline baggage. Self-organizing map neural networks proved more useful than principal components analysis.
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References
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© 1997 Springer-Verlag Wien
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Daniel, N.W., Lewis, I.R., Griffiths, P.R. (1997). Supervised and Unsupervised Methods of Classification of Raman Spectra of Explosives and Non-Explosives. In: Mink, J., Keresztury, G., Kellner, R. (eds) Progress in Fourier Transform Spectroscopy. Mikrochimica Acta Supplement, vol 14. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6840-0_58
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DOI: https://doi.org/10.1007/978-3-7091-6840-0_58
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