计算机应用研究2017，Vol.34Issue(10)：2881-2886,2891,7.DOI:10.3969/j.issn.1001-3695.2017.10.001
基于卷积神经网络的目标检测研究综述
Review of object detection based on convolutional neural networks
摘要
Abstract
With the increase of training data and the improvement of the performance of computers,the CNN-based object detection breaks the bottleneck of traditional object detection and has been the main method of current object detection.Therefore,it is a significant research that how to effectively utilize CNN for object detection.Firstly,this paper reviewed how to solve the problems of traditional object detection by CNN.Secondly,it introduced the basic architecture of CNN and described the current research development and widely-used CNN.Thirdly,this paper mainly analyzed and discussed two kinds of ideas and methods of the CNN-based object detection and pointed out the present deficiency.Finally,it concluded the CNN-based object detection and the future direction.关键词
卷积神经网络/目标检测/深度学习Key words
convolutional neural network(CNN)/object detection/deep learning分类
信息技术与安全科学引用本文复制引用
李旭冬,叶茂,李涛..基于卷积神经网络的目标检测研究综述[J].计算机应用研究,2017,34(10):2881-2886,2891,7.基金项目
国家自然科学基金资助项目(61375038) （61375038）
