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An Ensembled Neural Network Classifier for Vehicle Classification Using ILD
Published in Springer Berlin Heidelberg
Volume: 270 CCIS
Issue: PART II
Pages: 149 - 157
Vehicle classification is required to study various parameters related to traffic. It is impossible to estimate the density of vehicles, number of vehicle types etc. without vehicles classification. This paper reviews various neural network algorithms using single loop detector that can be used in real time traffic management system to classify vehicles. Since it is evident that neural network is a weak classifier, we propose a model which uses an ensembled neural network algorithm using ILD to achieve high speed and accuracy than the traditional method. © 2012 Springer-Verlag.
About the journal
JournalData powered by TypesetCommunications in Computer and Information Science Global Trends in Information Systems and Software Applications
PublisherData powered by TypesetSpringer Berlin Heidelberg
Open Access0