基于深度学习的目标检测研究与应用综述

Progress of Research and Application of Object Detection Based on Deep Learning

基于深度学习的目标检测算法相较于传统的目标检测算法,对复杂场景的稳健性更强,是当前研究的热点方向。根据基于深度学习的目标检测算法的流程特点将其分为两阶段目标检测算法和单阶段目标检测算法,着重介绍了部分经典算法所解决的问题及其优缺点,梳理了其在工业界的应用情况,对其存在的问题进行了讨论,对未来可能的发展趋势进行了展望。

Compared with traditional object detection algorithms,object detection algorithm based on deep learning is more robust to complex scenes,and is currently a hot research direction.It is divided into two-stage detection algorithm and one-stage detection algorithm according to the process characteristics of the object detection algorithm based on deep learning.The problems solved by some of the classic algorithms and their advantages and disadvantages are introduced.Its application in the industry is sorted out.The remaining problems are discussed,and the possible future development trends are further prospected.