深度卷积应用于目标检测算法综述  

Review of Deep Convolution Applied to Target Detection Algorithms

作　　者：董文轩 梁宏涛 刘国柱[1] 胡强[1] 于旭[1] DONG Wenxuan;LIANG Hongtao;LIU Guozhu;HU Qiang;YU Xu(School of Information Science and Technology,Qingdao University of Science and Technology,Qingdao,Shandong 266061,China)

机构地区：[1]青岛科技大学信息科学技术学院,山东青岛266061

出　　处：《计算机科学与探索》2022年第5期1025-1042,共18页Journal of Frontiers of Computer Science and Technology

基　　金：国家自然科学基金(61973180);山东省产教融合研究生联合培养示范基地项目(2020-19)。

摘　　要：目标检测作为计算机视觉中最基本、最具挑战性的任务之一,旨在找出图像中特定的目标,并对目标进行定位和分类,现已被广泛应用于工业质检、视频监控、无人驾驶等众多领域。近年来,随着计算机硬件资源和深度卷积算法在图像分类任务中取得突破性进展,基于深度卷积的目标检测算法也逐渐替代了传统的目标检测算法,在精度和性能方面取得了显著成果。综述了基于深度卷积的目标检测算法的研究现状以及今后可能的发展方向。以传统目标检测算法存在的局限性为引,首先介绍了目标检测算法权威的数据集和评估指标;再以时间和算法架构为研究主线,综述了近年来基于深度卷积的目标检测代表性算法的研究和发展历程,对比分析了单阶段、双阶段以及其他改进算法的网络架构,并归纳总结出各类目标检测算法所存在的特点、优势和局限;最后结合当下目标检测存在的问题与挑战对未来趋势进行展望。As one of the most fundamental and challenging tasks in computer vision,target detection aims to find out specific targets in images and to locate and classify them,and is now widely used in many fields such as industrial quality inspection,video surveillance and unmanned vehicles.In recent years,with the breakthroughs in computer hardware resources and depth convolution algorithms in image classification tasks,depth convolution-based target detection algorithms have gradually replaced the traditional target detection algorithms and achieved significant results in terms of accuracy and performance.This paper reviews the current research status of depth convolution based target detection algorithms and possible future development directions.It introduces the authoritative datasets and evaluation metrics of target detection algorithms with the limitations of traditional target detection algorithms as a guide,and then reviews the research and development history of representative algorithms for depth convolution based target detection in recent years with time and algorithm architecture as the main research lines.The network structures of one-stage,two-stage and other improved algorithms are compared and analyzed,and the characteristics,advantages and limitations of various target detection algorithms are summarized.Finally,the future trends are prospected in the light of current problems and challenges of target detection.

关 键 词：计算机视觉 深度卷积 目标检测 单阶段 双阶段 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]