Publication Type : Book Chapter
Publisher : SpringerLink
Source : Proceedings of ICICC 2022, Volume 2, pp. 185-192. Singapore: Springer Nature Singapore, 2022.
Url : https://link.springer.com/chapter/10.1007/978-981-19-2535-1_14
Campus : Coimbatore
School : School of Artificial Intelligence - Coimbatore
Year : 2022
Abstract : Automation of vehicle classification is essential in the establishment of effective Intelligent Transportation Systems (ITS). Based on the MIOvision Traffic Camera Dataset (MIO-TCD), this paper categorizes the types of vehicles as car, bus, van, light truck, motorcycle and multi-axle truck. The classification of surveillance images is achieved using an ensemble of Deep Networks. Three networks are trained separately to make up the deep learning ensemble model with ConvNet, LeNet and EfficientNet achieving 89%, 68% and 87% classification accuracy, respectively. Results of experiments unveil that the ensemble of networks outperforms the individual networks. The ensemble of networks achieves 92.77%, which is high when compared to the performance based on genetic method in the recent literature.
Cite this Research Publication : Asmitha, U., S. Roshan Tushar, V. Sowmya, and K. P. Soman. "Ensemble Deep Learning Models for Vehicle Classification in Motorized Traffic Analysis." In International Conference on Innovative Computing and Communications: Proceedings of ICICC 2022, Volume 2, pp. 185-192. Singapore: Springer Nature Singapore, 2022.