Detection and classification of road signs in raining condition with limited dataset
Author:
Funder
Universiti Malaya
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Signal Processing
Link
https://link.springer.com/content/pdf/10.1007/s11760-022-02414-w.pdf
Reference14 articles.
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2. Palak, Sangal AL: Traffic signs classification using convolutional neural networks: a review. In: 2021 2nd International Conference on Secure Cyber Computing and Communications (ICSCCC), pp. 450–455 (2021). https://doi.org/10.1109/ICSCCC51823.2021.9478172
3. Yang, W., Zhang, W.: Real-time traffic signs detection based on YOLO network model. In: 2020 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), pp. 354–357 (2020). https://doi.org/10.1109/CyberC49757.2020.00066
4. Islam, Kh.T., Raj, R.G.: Real-time (vision-based) road sign recognition using an artificial neural network. Sensors (Basel, Switzerland) 17(4), 853 (2017). https://doi.org/10.3390/s17040853
5. Zheng, Z., Zhang, H., Wang, B., Gao, Z.: Robust traffic sign recognition and tracking for Advanced Driver Assistance Systems. In: 2012 15th International IEEE Conference on Intelligent Transportation Systems, pp. 704–709 (2012). https://doi.org/10.1109/ITSC.2012.6338799.
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1. Multistage traffic sign recognition under harsh environment;Multimedia Tools and Applications;2024-03-06
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