Bingyi Ren1,4, Juwei Zhang2,3,4,*, Tong Wang2,4
CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1425-1440, 2024, DOI:10.32604/cmc.2024.052667
Abstract Autonomous driving technology has entered a period of rapid development, and traffic sign detection is one of the important tasks. Existing target detection networks are difficult to adapt to scenarios where target sizes are seriously imbalanced, and traffic sign targets are small and have unclear features, which makes detection more difficult. Therefore, we propose a Hybrid Feature Fusion Traffic Sign detection algorithm based on YOLOv7 (HFFT-YOLO). First, a self-attention mechanism is incorporated at the end of the backbone network to calculate feature interactions within scales; Secondly, the cross-scale fusion part of the neck introduces a… More >
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