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Classification of R...
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Butt, NaveedLund University,Lunds universitet,Matematisk statistik,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,Mathematical Statistics,Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH
(author)
Classification of Raman Spectra to Detect Hidden Explosives
- Article/chapterEnglish2011
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LIBRIS-ID:oai:lup.lub.lu.se:db08f99f-a046-458c-819d-751e78bf6312
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https://lup.lub.lu.se/record/1691407URI
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https://doi.org/10.1109/LGRS.2010.2089970DOI
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https://urn.kb.se/resolve?urn=urn:nbn:se:bth-7543URI
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Language:English
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Summary in:English
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Raman spectroscopy is a laser-based vibrational technique that can provide spectral signatures unique to a multitude of compounds. The technique is gaining widespread interest as a method for detecting hidden explosives due to its sensitivity and ease of use. In this letter, we present a computationally efficient classification scheme for accurate standoff identification of several common explosives using visible-range Raman spectroscopy. Using real measurements, we evaluate and modify a recent correlation-based approach to classify Raman spectra from various harmful and commonplace substances. The results show that the proposed approach can, at a distance of 30 m, or more, successfully classify measured Raman spectra from several explosive substances, including nitromethane, trinitrotoluene, dinitrotoluene, hydrogen peroxide, triacetone triperoxide, and ammonium nitrate.
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Nilsson, Mikael
(author)
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Jakobsson, AndreasLund University,Lunds universitet,Biomedical Modelling and Computation,Forskargrupper vid Lunds universitet,Statistical Signal Processing Group,Matematisk statistik,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,Lund University Research Groups,Mathematical Statistics,Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH(Swepub:lu)mats-aaj
(author)
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Nordberg, Magnus
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Pettersson, Anna
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Wallin, Sara
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Östmark, Henric
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Matematisk statistikMatematikcentrum
(creator_code:org_t)
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In:IEEE Geoscience and Remote Sensing Letters: IEEE8:3, s. 517-5211545-598X
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