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基於Yolov4算法的交通標誌檢測

Traffic sign detection based on Yolov4 and its improved algorithm

  • 摘要: 為了提高交通標誌識別的速度和精度,提出了一種采用Yolov4(You only look once version 4)深度學習框架的交通標誌識別方法🟪,並將該方法與SSD(single shot multi box detector)和Yolov3(You only look once version 3)算法進行對比,所提算法模型參數量顯著增加。進一步對Yolov4的主幹特征提取網絡和多尺度輸出進行調整,提出輕量化的Yolov4算法。仿真實驗表明,此算法能夠快速有效檢測交通標誌,具有實時性和適用性。

     

    Abstract: In order to improve the speed and accuracy of the vehicle perception system in recognizing traffic signs, a traffic sign recognition method using the Yolov4 (You only look once version 4) deep learning framework was proposed. This method was compared with the single shot multi box detector (SSD) and Yolov3 (You only look once version 3) algorithms, which showed that parameters of the proposed algorithm model had increased significantly. The backbone feature extraction network and multi-scale output of Yolov4 were further adjusted by the algorithm. And a lightweight Yolov4 algorithm was proposed. Experimental results showed that the improved algorithm could effectively detect traffic signs, and had good real-time performance and applicability.

     

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