深度学习中的安全帽检测算法应用研究综述

doi:10.3778/j.issn.1002-8331.2203-0580

摘要/Abstract

摘要： 安全帽是施工现场最常见和实用的个人防护工具，能够有效防止和减轻意外带来的头部伤害。安全帽检测是施工现场人员安全管理的主要工作，也是施工现场智能化监控技术的重要内容，随着深度学习的发展，现已成为智慧工地建设的重要部分。为了综合分析深度学习在安全帽检测中的研究现状，针对安全帽检测算法研究，归纳了常用的安全帽检测算法和基于深度学习的安全帽检测算法，具体说明了其优缺点。在此基础上，针对现有问题，系统地总结分析了安全帽检测算法的相关改进方法，并梳理了各类方法的特点、优势和局限性。最后展望了基于深度学习的安全帽检测算法的未来发展方向。

关键词: 深度学习, 安全帽检测, 目标检测, 智慧工地

Abstract: Safety helmet is the most common and practical personal protective tool on the construction site, which can effectively prevent and reduce head injury caused by accidents. Helmet detection is the main work of personnel safety management on the construction site, and it is also an important content of intelligent monitoring technology on the construction site. With the development of deep learning, it has become an important part of smart site construction. In order to comprehensively analyze the research status of deep learning in helmet detection, aiming at the research of helmet detection algorithm, the commonly used helmet detection algorithm and helmet detection algorithm based on deep learning are summarized, and their advantages and disadvantages are explained in detail. On this basis, aiming at the existing problems, this paper systematically summarizes and analyzes the relevant improvement methods of helmet detection algorithm, and combs the characteristics, advantages and limitations of various methods. Finally, the future development direction of helmet detection algorithm based on deep learning is prospected.

Key words: deep learning, helmet detection, target detection, smart construction site

张立艺, 武文红, 牛恒茂, 石宝, 段凯博, 苏晨阳. 深度学习中的安全帽检测算法应用研究综述[J]. 计算机工程与应用, 2022, 58(16): 1-17.

ZHANG Liyi, WU Wenhong, NIU Hengmao, SHI Bao, DUAN Kaibo, SU Chenyang. Summary of Application Research on Helmet Detection Algorithm Based on Deep Learning[J]. Computer Engineering and Applications, 2022, 58(16): 1-17.

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