Traffic Sign Recognition Based on Convolutional Neural Network
As a research hotspot in automatic driving and intelligent transportation,traffic sign recognition is crucial for traffic safety in the car networking environment.To overcome the technical difficulties of conventional traffic sign recognition methods such as multiple types,complex shapes,and accuracy affected by changes in lighting,this paper constructs a traffic sign recognition model based on the convolutional neural network to realize the fast and accurate recognition of traffic signs.The research results show that the proposed convolutional neural network model can accurately recognize 10 types of traffic signs and has a good generalization ability and robustness.The research could lay the foundation for the development of traffic safety and intelligent transportation in the future.
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