[1]伍锡如,雪刚刚.基于图像聚类的交通标志CNN快速识别算法[J].智能系统学报,2019,14(4):670-678.[doi:10.11992/tis.201806026]
 WU Xiru,XUE Ganggang.CNN-based image clustering algorithm for fast recognition of traffic signs[J].CAAI Transactions on Intelligent Systems,2019,14(4):670-678.[doi:10.11992/tis.201806026]
点击复制

基于图像聚类的交通标志CNN快速识别算法

参考文献/References:
[1] SAADNA Y, BEHLOUL A. An overview of traffic sign detection and classification methods[J]. International journal of multimedia information retrieval, 2017, 6(3):193-210.
[2] BERKAYA S K, GUNDUZ H, OZSEN O, et al. On circular traffic sign detection and recognition[J]. Expert systems with applications, 2016, 48:67-75.
[3] HOFERLIN B, ZIMMERMANN K. Towards reliable traffic sign recognition[C]//2009 IEEE Intelligent Vehicles Symposium. Xi’an, China, 2009:324-329.
[4] 张卡, 盛业华, 叶春, 等. 基于中心投影形状特征的车载移动测量系统交通标志自动识别[J]. 仪器仪表学报, 2010, 31(9):2101-2108 ZHANG Ka, SHENG Yehua, YE Chun, et al. Automatic recognition of road traffic sign based on central projected shape feature for vehicle-borne mobile mapping system[J]. Chinese journal of scientific instrument, 2010, 31(9):2101-2108
[5] LU Ke, DING Zhengming, GE S. Sparse-representation-based graph embedding for traffic sign recognition[J]. IEEE transactions on intelligent transportation systems, 2012, 13(4):1515-1524.
[6] 宋文杰, 付梦印, 杨毅. 一种面向无人驾驶汽车的高效交通标志识别方法[J]. 机器人, 2015, 37(1):102-111 SONG Wenjie, FU Mengyin, YANG Yi. An efficient traffic signs recognition method for autonomous vehicle[J]. Robot, 2015, 37(1):102-111
[7] HINTON G E, OSINDERO S, TEH Y W. A fast learning algorithm for deep belief nets[J]. Neural computation, 2006, 18(7):1527-1554.
[8] HINTON G E, SALAKHUTDINOV R R. Reducing the dimensionality of data with neural networks[J]. Science, 2006, 313(5786):504-507.
[9] LECUN Y, BENGIO Y, HINTON G. Deep learning[J]. Nature, 2015, 521(7553):436-444.
[10] 刘方园, 王水花, 张煜东. 深度置信网络模型及应用研究综述[J]. 计算机工程与应用, 2018, 54(1):11-18 LIU Fangyuan, WANG Shuihua, ZHANG Yudong. Survey on deep belief network model and its applications[J]. Computer engineering and applications, 2018, 54(1):11-18
[11] GOLOVKO V A. Deep learning:an overview and main paradigms[J]. Optical memory and neural networks, 2017, 26(1):1-17.
[12] 马志强, 李图雅, 杨双涛, 等. 基于深度神经网络的蒙古语声学模型建模研究[J]. 智能系统学报, 2018, 13(3):486-492 MA Zhiqiang, LI Tuya, YANG Shuangtao, et al. Mongolian acoustic modeling based on deep neural network[J]. CAAI transactions on intelligent systems, 2018, 13(3):486-492
[13] CIRE?AN D, MEIER U, MASCI J, et al. Multi-column deep neural network for traffic sign classification[J]. Neural networks, 2012, 32:333-338.
[14] 孙伟, 杜宏吉, 张小瑞, 等. 基于CNN多层特征和ELM的交通标志识别[J]. 电子科技大学学报, 2018, 47(3):343-349 SUN Wei, DU Hongji, ZHANG Xiaorui, et al. Traffic sign recognition method based on multi-layer feature CNN and extreme learning machine[J]. Journal of University of Electronic Science and Technology of China, 2018, 47(3):343-349
[15] CHAWLA N V. Data mining for imbalanced datasets:An overview[M]//MAIMON O, ROKACH L. Data Mining and Knowledge Discovery Handbook. Boston, MA:Springer, 2005:853-867.
[16] LECUN Y, BOTTOU L, BENGIO Y, et al. Gradient-based learning applied to document recognition[J]. Proceedings of the IEEE, 1998, 86(11):2278-2324.
[17] MURTAGH F. A survey of recent advances in hierarchical clustering algorithms[J]. The computer journal, 1983, 26(4):354-359.
[18] PAL N R. A primer on cluster analysis:4 basic methods that (usually) work[book review] [J]. IEEE computational intelligence magazine, 2017, 12(4):98-100.
[19] ZAKLOUTA F, STANCIULESCU B. Real-time traffic-sign recognition using tree classifiers[J]. IEEE transactions on intelligent transportation systems, 2012, 13(4):1507-1514.
[20] SERMANET P, LECUN Y. Traffic sign recognition with multi-scale convolutional networks[C]//2011 International Joint Conference on Neural Networks. San Jose, CA, USA, 2011:2809-2813.
相似文献/References:
[1]程显毅,陈小波.基于多Agent的模式识别框[J].智能系统学报,2006,1(2):89.
 CHENG Xian-yi,CHEN Xiao-bo.Frame of pattern recognition based on multi-Agent[J].CAAI Transactions on Intelligent Systems,2006,1():89.
[2]杨静宇,郑宇杰.基于QR分解的鉴别维数压缩及其在人脸识别中的应用[J].智能系统学报,2007,2(6):48.
 YANG Jing-yu,ZHENG Yu-jie.Discriminant dimensionality reduction based on QR decomposition and its application in face recognition[J].CAAI Transactions on Intelligent Systems,2007,2():48.
[3]叶果,程洪,赵洋.电影中吸烟活动识别[J].智能系统学报,2011,6(5):440.
 YE Guo,CHENG Hong,ZHAO Yang.moking recognition in movies[J].CAAI Transactions on Intelligent Systems,2011,6():440.
[4]陈阳,覃鸿,李卫军,等.仿生模式识别技术研究与应用进展[J].智能系统学报,2016,11(1):1.[doi:10.11992/tis.201506011]
 CHEN Yang,QIN Hong,LI Weijun,et al.Progress in research and application of biomimetic pattern recognition technology[J].CAAI Transactions on Intelligent Systems,2016,11():1.[doi:10.11992/tis.201506011]
[5]杨钟亮,陈育苗.基于GGA-Elman网络的头部体态语言sEMG识别[J].智能系统学报,2014,9(4):385.[doi:10.3969/j.issn.1673-4785.201310047]
 YANG Zhongliang,CHEN Yumiao.An sEMG approach to recognize the body language of the head based on the GGA-Elman network[J].CAAI Transactions on Intelligent Systems,2014,9():385.[doi:10.3969/j.issn.1673-4785.201310047]
[6]李欢,王士同.支持向量机的多观测样本二分类算法[J].智能系统学报,2014,9(4):392.[doi:10.3969/j.issn.1673-4785.201312040]
 LI Huan,WANG Shitong.Binary-class classification algorithm with multiple-access acquired objects based on the SVM[J].CAAI Transactions on Intelligent Systems,2014,9():392.[doi:10.3969/j.issn.1673-4785.201312040]
[7]倪怀发,沈肖波,孙权森.基于低秩分解的鲁棒典型相关分析[J].智能系统学报,2017,12(4):491.[doi:10.11992/tis.201607024]
 NI Huaifa,SHEN Xiaobo,SUN Quansen.Robust canonical correlation analysis based onlow rank decomposition[J].CAAI Transactions on Intelligent Systems,2017,12():491.[doi:10.11992/tis.201607024]
[8]李德毅.AI——人类社会发展的加速器[J].智能系统学报,2017,12(5):583.[doi:10.11992/tis.201710016]
 LI Deyi.Artificial intelligence:an accelerator for the development of human society[J].CAAI Transactions on Intelligent Systems,2017,12():583.[doi:10.11992/tis.201710016]
[9]葛园园,许有疆,赵帅,等.自动驾驶场景下小且密集的交通标志检测[J].智能系统学报,2018,13(3):366.[doi:10.11992/tis.201706040]
 GE Yuanyuan,XU Youjiang,ZHAO Shuai,et al.Detection of small and dense traffic signs in self-driving scenarios[J].CAAI Transactions on Intelligent Systems,2018,13():366.[doi:10.11992/tis.201706040]
[10]冯小荣,惠康华,柳振东.基于卷积特征和贝叶斯分类器的人脸识别[J].智能系统学报,2018,13(5):769.[doi:10.11992/tis.201706052]
 FENG Xiaorong,HUI Kanghua,LIU Zhendong.Face recognition based on convolution feature and Bayes classifier[J].CAAI Transactions on Intelligent Systems,2018,13():769.[doi:10.11992/tis.201706052]

备注/Memo

收稿日期:2018-06-12。
基金项目:国家自然科学基金项目(61603107,61863007);省部共建药用资源化学与药物分子工程国家重点实验室项目(NCOC2016-B01);广西研究生教育创新计划项目(YCSW2017144);桂林电子科技大学研究生教育创新计划项目(2017YJCX88,2018YJCX76).
作者简介:伍锡如,男,1981年生,副教授,博士,主要研究方向为非线性系统控制、神经网络、机器人控制。参与国家863计划,参与或负责多个国家自然科学基金项目。获国家发明专利5项;雪刚刚,男,1992年生,硕士研究生,主要研究方向为深度学习、计算机视觉。
通讯作者:雪刚刚.E-mail:stayrealxue@163.com

更新日期/Last Update: 2019-08-25
Copyright @ 《 智能系统学报》 编辑部
地址:(150001)黑龙江省哈尔滨市南岗区南通大街145-1号楼 电话:0451- 82534001、82518134