RT Conference Proceedings
T1 Vehicle Type Detection by Convolutional Neural Networks
A1 Molina-Cabello, Miguel Ángel
A1 Luque-Baena, Rafael Marcos
A1 López-Rubio, Ezequiel
A1 Thurnhofer-Hemsi, Karl
K1 Redes neuronales (Informática)
AB In this work a new vehicle type detection procedure for traffic surveillance videos is proposed. A Convolutional Neural Network isintegrated into a vehicle tracking system in order to accomplish this task.Solutions for vehicle overlapping, differing vehicle sizes and poor spatial resolution are presented. The system is tested on well known benchmarks, and multiclass recognition performance results are reported. Our proposal is shown to attain good results over a wide range of difficultsituations.
PB Springer
YR 2017
FD 2017
LK http://hdl.handle.net/10630/14114
UL http://hdl.handle.net/10630/14114
LA eng
NO J.M. Ferrández Vicente et al. (Eds.): IWINAC 2017, Part II, LNCS 10338, pp. 268–278, 2017. DOI: 10.1007/978-3-319-59773-728
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026