基于深度学习的目标检测系统性文献综述  

A Systematic Literature Review of Object Detection Based on Deep Learning

作　　者：李坤坤 刘正熙[1] 熊运余[1] LI Kunkun;LIU Zhengxi;XIONG Yunyu(College of Computer Science,Sichuan University,Chengdu 610065)

机构地区：[1]四川大学计算机学院,成都610065

出　　处：《现代计算机》2021年第16期98-102,117,共6页Modern Computer

摘　　要：近年来,随着深度学习技术的快速发展,基于深度学习的目标检测研究不断涌现。通过采用系统性文献综述方法对目标检测领域的156篇文献进行回顾,梳理出目标检测领域四个不同的研究问题,并对目标检测应用、数据集、主流深度卷积神经网络模型和框架进行总结。In recent years,with the rapid development of deep learning technology,object detection research based on deep learning is emerging.A sys-tematic literature review method is used to review 156 research papers in the field of object detection.Four different research issues in the field of object detection are sorted out,and object detection applications,data sets,mainstream deep convolution neural network models and frameworks are summarized.

关 键 词：目标检测 深度学习 模型 框架 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TP18[自动化与计算机技术—计算机科学与技术]