Traffic Sign Recognition Using Deep Convolutional Networks and Extreme Learning Machine
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-319-23989-7_28
Reference24 articles.
1. Stallkamp, J., Schlipsing, M., Salmen, J., Igel, C.: The German traffic sign recognition benchmark: a multi-class classification competition. In: Proceedings of International Joint Conference on Neural Networks, pp. 1453–1460 (2011)
2. Stallkamp, J., Schlipsing, M., Salmen, J., Igel, C.: Man vs. computer: benchmarking machine learning algorithms for traffic sign recognition. Neural Netw. 32, 323–332 (2012)
3. Ruta, A., Li, Y.M., Liu, X.H.: Robust class similarity measure for traffic sign recognition. IEEE Trans. Intell. Transp. Syst. 11, 847–855 (2010)
4. Zaklouta, F., Bogdan, S., Hamdoun, O.: Traffic sign classification using kd trees and random forests. In: The 2011 International Joint Conference on Neural Networks (IJCNN). IEEE (2011)
5. Razavian, A.S., et al.: CNN features off-the-shelf: an astounding baseline for recognition. arXiv preprint arXiv:1403.6382 (2014)
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