This paper provides an overview of the current state and challenges in helmet-wearing detection technology,with a particular focus on the application potential of deep learning methodologies,notably the YOLO(You Only Look Once)series of algorithms,in the realm of helmet recognition.By implementing the YOLOv8 algorithm for helmet-wearing detection,this approach not only overcomes the limitations of conventional surveillance methods but also achieves highly efficient and accurate automated detection.It thereby significantly contributes to the implementation of the"One Helmet,One Belt"safety campaign and enhances public safety management capabilities.
维普
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