Measuring the Efficiencies of Vehicle Classification Algorithms on Traffic Surveillance Video

Abstract— Traffic management and information systems
need to obtain information about traffic with various sensors
to control the traffic follow properly. In this context, videos
are very actively used in traffic surveillance and control in
recent years. With the help of image processing based video
surveillance system in traffic management systems, many
studies are done. In this study, we propose a traffic
management infrastructure for classification of vehicle
imaginaries. The effectiveness of artificial neural networks,
Adaboost, and support vector machines will be tested on
data sets we create.


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