南华大学学报（自然科学版）2016，Vol.30Issue(3)：66-72,7.
卷积神经网络的研究进展综述
Review of Convolution Neural Network
摘要
Abstract
Deep learning theory has received extensive attention of scholars all over the world because of its powerful modeling and high representational abilities.It solved the key problems of pattern recognition,such as the insufficiency of expression ability and dimen-sionality curse. Convolutional neural network ( CNN ) is a successful component of deep learning,which imitates the biological vision system. Local receptive field,sharing weights and down sampling are three important characteristics of CNN which lead it to be the hots-pot in the field of intelligent machine vision.Therefore,this paper summarizes the latest re-search works of CNN. Firstly, the history of CNN is introduced. Secondly, state-of-the-art modified models of CNN are reviewed.Then,the applications of CNN in speech,image and video processing are illustrated.Finally,the development trends of CNN are concluded.关键词
深度学习/卷积神经网络/特征提取/智能识别Key words
deep learning/convolutional neural network/feature extraction/intelligent rec-ognition分类
信息技术与安全科学引用本文复制引用
杨斌,钟金英..卷积神经网络的研究进展综述[J].南华大学学报（自然科学版）,2016,30(3):66-72,7.基金项目
南华大学青年英才支持计划基金资助项目(聘字2014-004号)；国家自然科学基金资助项目(61102108)；南华大学校内博士启动基金资助项目(2011XQD29)；湖南省优秀博士学位论文基金资助项目( YB2013B039) （聘字2014-004号）
