Deep learning has developed rapidly and made unprecedented achievements especially in the field of image cognition, since Alex et al. proposed AlexNet in 2012. This paper focuses on the mainstream research methods of traffic sign detection and recognition, including the traditional feature-based image processing method and the target detection method based on deep learning. The traffic sign detection and recognition method based on deep learning is divided into two categories for discussion and analysis, namely, the Anchor based and Anchor-Free neural network architectures. Finally, the paper makes a brief summary and prospects the future development.
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