基于深度学习的头盔佩戴检测方法研究

Research on helmet-wearing detection methods based on deep learning

文章综述了当前头盔佩戴检测技术的发展现状与挑战,重点探讨了基于深度学习方法尤其是YOLO系列算法在头盔佩戴识别领域的应用潜力。文章将YOLOv8算法应用于头盔佩戴检测领域,此方法克服了传统监控手段的局限性,实现了高效率、高准确率的自动检测,对于推动“一盔一带”安全守护行动的实施和提升公共安全管理水平具有重要价值。

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.