基于深度学习的目标检测算法综述

Survey of object detection algorithm based on deep learning

目标检测是高级视觉研究领域的重要前提,是计算机视觉研究的核心问题。深度学习拥有强大的自学习能力,将其运用至目标检测领域能够在一定程度上弥补了传统检测方法的不足。首先介绍了传统目标检测方法面临的困境;然后对两阶段深度学习算法和单阶段深度学习算法分别进行介绍;最后对基于深度学习的目标检测算法的发展进行总结,并对未来前景进行了展望。

Object detection is an important prerequisite in the field of advanced vision research and the core issue of computer vision research.Deep learning has a strong self-learning ability,and its application to the field of target detection can make up for the deficiencies of traditional detection methods to a certain extent.The article first introduces the dilemma faced by traditional detection methods;then the two-stage deep learning algorithms(and single-stage deep learning algorithms introduce separately;finally summarize the development of target detection algorithm based on deep learning and look forward to the future prospects.