Traffic Sign Detection and Recognition Using Deep Learning Approach
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-34619-4_27
Reference15 articles.
1. Toh, C.K., Cano, J.C., Fernandez-Laguia, C., et al.: Wireless digital traffic signs of the future. IET Netw. 8, 74–78 (2019). https://doi.org/10.1049/IET-NET.2018.5127
2. Rayed, A.M., Ur, M.A., Tariq, R., et al.: An analysis of driving behavior of educated youth in Bangladesh considering physiological, cultural and socioeconomic variables (2022). https://doi.org/10.3390/su14095134
3. Bénallal, M., Meunier, J.: Real-time color segmentation of road signs. In: Canadian Conference on Electrical and Computer Engineering, vol. 3, pp. 1823–1826 (2003). https://doi.org/10.1109/CCECE.2003.1226265
4. Liu, Y.S., Duh, D.J., Chen, S.Y., et al.: Scale and skew-invariant road sign recognition. Int. J. Imaging Syst Technol 17, 28–39 (2007). https://doi.org/10.1002/IMA.20095
5. De la Escalera, A., Armingol, J.M., Mata, M.: Traffic sign recognition and analysis for intelligent vehicles. Image Vis. Comput. 21, 247–258 (2003). https://doi.org/10.1016/S0262-8856(02)00156-7
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