dc.contributor.author | Kathriarachchi, RPS | |
dc.contributor.author | Gunesekera, ADAI | |
dc.contributor.author | Silva, KC | |
dc.contributor.author | Gunesekera, Y | |
dc.date.accessioned | 2018-05-21T08:35:17Z | |
dc.date.available | 2018-05-21T08:35:17Z | |
dc.date.issued | 2015 | |
dc.identifier.uri | http://ir.kdu.ac.lk/handle/345/1093 | |
dc.description | Article Full Text | en_US |
dc.description.abstract | Security is a foremost concern especially in Military domains. Therefore it is compulsory to have proper scrutinizing procedures at entrance of any military premises. Presently military bases practice highly manual base security scrutinizing process. The present process causes number of overheads to administration of respective military base, because it raises delays and creates frustration on parties engaged with security checking at entrance. Also there are complications in identifying key passengers. This research intended to investigate present issue and expected to find available solutions under Neural Network backgrounds. The research proposes a model which integrates Automatic Face Recognition (AFR) and Automatic Number Plate Recognition (ANPR) technologies to overcome aforesaid issue. Scientific research methodology was key methodology chosen for the research and this research has tailored Meta-analysis approach with scientific research methodology to draw out a proper model as solution. Scientific research methodology sparks research with close observation of a problem and generates a clearly defined problem after proper preliminary investigation. Based on the identified problem the research generates hypothesis which leads to an experimental design to output a fine tuned solution. Meta-analysis brings a thorough examination at preliminary investigation and identifies possibilities of merging different research outcomes from previous researches to draw a novel solution for the problem. As per research outcome, it is evident that there are number of research done in ANPR systems and few done in face recognition systems in Sri Lankan context. Also it is evident that there are no solutions implemented with integration of these two technologies for military domains. Therefore this research emphasizes that it is vital to implement a solution for military bases which behave as a smart entrance tracking system. The key outcome it proposes is an architectural model for the system. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Number Plate Recognition | en_US |
dc.subject | Automatic Face Recognition | en_US |
dc.subject | Real Time Image Processing | en_US |
dc.title | Smart Entrance Tracking Using Artificial Neural Network Technology: A Meta-Analysis on Military bases in Sri Lanka | en_US |
dc.type | Article Full Text | en_US |
dcterms.bibliographicCitation | Kathriarachchi, R. P. S. et al. (2015) ‘Smart Entrance Tracking Using Artificial Neural Network Technology : A Meta-Analysis on Military bases in Sri Lanka’, in KDU International Research Symposium Proceedings. General Sir John Kotelawala Defence University, pp. 183–188. Available at: http://ir.kdu.ac.lk/handle/345/1093. | |
dc.identifier.journal | KDU IRC | en_US |
dc.identifier.pgnos | 183-188 | en_US |