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Description
  • The paper describes neural network classification of specific audio sources into given categories. Audio sources are represented by various gunshots, from handguns or big bore guns. This article is a follow-up to an existing system for localization of audio sources from security and military areas. The question of successful classification lies in the convenient discrimination of the feature vector in the feature vector space. A set of feature vectors based on power spectral density is evaluated a tested for the best classification of gunshots.
  • The paper describes neural network classification of specific audio sources into given categories. Audio sources are represented by various gunshots, from handguns or big bore guns. This article is a follow-up to an existing system for localization of audio sources from security and military areas. The question of successful classification lies in the convenient discrimination of the feature vector in the feature vector space. A set of feature vectors based on power spectral density is evaluated a tested for the best classification of gunshots. (en)
Title
  • Neural network classification of gunshots using spectral characteristics
  • Neural network classification of gunshots using spectral characteristics (en)
skos:prefLabel
  • Neural network classification of gunshots using spectral characteristics
  • Neural network classification of gunshots using spectral characteristics (en)
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  • RIV/70883521:28140/11:43865874!RIV12-MSM-28140___
http://linked.open...avai/riv/aktivita
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  • P(ED2.1.00/03.0089), Z(MSM7088352102)
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  • 215651
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  • RIV/70883521:28140/11:43865874
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  • Neural network, classification, gunshots, spectral analysis, feature vector (en)
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  • [D9BC0937583C]
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  • Lanzarote
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  • Recent Researches in Automatic Control
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  • Navrátil, Milan
  • Dostálek, Petr
  • Křesálek, Vojtěch
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http://linked.open...n/vavai/riv/zamer
number of pages
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  • WSEAS Press
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  • 978-1-61804-004-6
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  • 28140
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