| dc.contributor.author | Ahmad Kadri, Junoh | |
| dc.contributor.author | Muhammad Naufal, Mansor | |
| dc.date.accessioned | 2014-04-21T03:52:18Z | |
| dc.date.available | 2014-04-21T03:52:18Z | |
| dc.date.issued | 2013 | |
| dc.identifier.citation | Advances in Intelligent Systems and Computing, vol. 206 AISC, 2013, pages 655-660 | en_US |
| dc.identifier.isbn | 978-364236980-3 | |
| dc.identifier.issn | 2194-5357 | |
| dc.identifier.uri | http://link.springer.com/chapter/10.1007%2F978-3-642-36981-0_60 | |
| dc.identifier.uri | http://dspace.unimap.edu.my:80/dspace/handle/123456789/33873 | |
| dc.description | Link to publisher's homepage at http://link.springer.com/ | en_US |
| dc.description.abstract | A 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.iso | en | en_US |
| dc.publisher | Springer-Verlag | en_US |
| dc.subject | Crime rate | en_US |
| dc.subject | Feed Forward Neural Network | en_US |
| dc.subject | Genetic Algorithm Neural Network | en_US |
| dc.subject | Local Binary Pattern | en_US |
| dc.title | New crime detection with LBP and GANN | en_US |
| dc.type | Article | en_US |
| dc.contributor.url | kadri@unimap.edu.my | en_US |
| dc.contributor.url | apairia@yahoo.com | en_US |
