苏山杰,陈俊豪,张之云

• 1:重庆交通大学机电与车辆工程学院

摘要(Abstract)：

近20年来，随着以物联网技术，计算机视觉技术为代表的核心技术蓬勃发展，基于深度学习的目标检测算法在各个领域都受到了较高的重视，而车辆目标检测是基于深度学习的目标检测中的一个重要研究领域，也是应用在智能驾驶、智能交通系统中非常重要的一部分。针对车辆目标检测任务，首先对深度学习的车辆目标检测进一步探讨，提出检测任务的重点、难点及发展现状，以时间线对卷积神经网络下车辆目标检测算法进行概括，并对目前2种主流的基于候选框和基于回归的车辆目标检测算法进行总结。伴随着目标检测算法的更加轻量化，检测性能更加优越，将在嵌入式设备得到应用，以提高检测任务的效率。在未来自动驾驶，智能交通系统领域对于安全性，实时性的要求会更高，使得车辆目标检测算法有较好的发展前景。

关键词(KeyWords)：

Abstract:

Keywords:

基金项目(Foundation):

作者(Author): 苏山杰,陈俊豪,张之云

DOI: 10.19822/j.cnki.1671-6329.20220011

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