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dc.contributor.authorAhmad Kadri, Junoh-
dc.contributor.authorMuhammad Naufal, Mansor-
dc.date.accessioned2014-04-21T03:52:18Z-
dc.date.available2014-04-21T03:52:18Z-
dc.date.issued2013-
dc.identifier.citationAdvances in Intelligent Systems and Computing, vol. 206 AISC, 2013, pages 655-660en_US
dc.identifier.isbn978-364236980-3-
dc.identifier.issn2194-5357-
dc.identifier.urihttp://link.springer.com/chapter/10.1007%2F978-3-642-36981-0_60-
dc.identifier.urihttp://dspace.unimap.edu.my:80/dspace/handle/123456789/33873-
dc.descriptionLink to publisher's homepage at http://link.springer.com/en_US
dc.description.abstractA current review of media sources indicates crimes of opportunity such as burglaries, purse-snatchings and vehicle theft, are consistently the most topical crime problems. The Malaysian government has taken several steps to increase police effectiveness and reduce crime since 2004. But their effectiveness is limited by low salaries and lack of manpower. Verily to compile a comprehensive afford of crime fighting capabilities. We present an explicit system to detect a crime scene with Local Binary Pattern (LBP) and a fusion of Genetic Algorithm with Neural Network (GANN). This system provided a good justification as a monitoring supplementary tool for the Malaysian police arm forced.en_US
dc.language.isoenen_US
dc.publisherSpringer-Verlagen_US
dc.subjectCrime rateen_US
dc.subjectFeed Forward Neural Networken_US
dc.subjectGenetic Algorithm Neural Networken_US
dc.subjectLocal Binary Patternen_US
dc.titleNew crime detection with LBP and GANNen_US
dc.typeArticleen_US
dc.contributor.urlkadri@unimap.edu.myen_US
dc.contributor.urlapairia@yahoo.comen_US
Appears in Collections:Institute of Engineering Mathematics (Articles)

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