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《Electronic Technology》 2017-06
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Pedestrian detection based on machine learning

Tao Zheng-rong;Jiangsu Automation Research Insititute;  
Pedestrian Detection is the computer for a given image and video, it is determined whether there were pedestrians, if there is also need to give the specific location of pedestrians. Pedestrian Detection is a pedestrian tracking, behavior analysis, gait analysis, identification of pedestrians and other research foundation and prerequisite for a good pedestrian detection algorithms can provide strong support and protection for the latter. This paper selects SVM machine learning and deep learning framework caffe of Imagenet model analysis and realization, and then compare the recognition rate of test performance comparison between the two, finally, got the deep learning have a better performance than machine learning.
【CateGory Index】: TP181;TP391.41
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Chinese Journal Full-text Database 2 Hits
1 GUO Li-li;DING Shi-fei;School of Computer Science and Technology,China University of Mining and Technology;Key Laboratory of Intelligent Information Processing,Institute of Computing Technology,Chinese Academy of Sciences;;Research Progress on Deep Learning[J];计算机科学;2015-05
2 Zheng Yin;Chen Quanqi;Zhang Yujin;Department of Electronic Engineering,Tsinghua University;;Deep learning and its new progress in object and behavior recognition[J];中国图象图形学报;2014-02
Chinese Journal Full-text Database 9 Hits
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2 Pian Zhaoyu;Shi Tianyu;Yuan Depeng;Hu Yulan;Wang Dong;School of Information Science and Engineering, Shenyang Ligong University;School of Computer Science and Engineering, Northeastern University;;Application of Hierarchical Visual Perception in Target Recognition[J];计算机辅助设计与图形学学报;2017-06
3 LV Jing;GAO Chenqiang;DU Yinhe;CHENG Hua;Chongqing Key Laboratory of Signal and Information Processing,Chongqing University of Posts and Telecommunications;China Ship Development and Design Center;;Infrared action recognition method based on adaptive fusion of dual channel features[J];重庆邮电大学学报(自然科学版);2017-03
4 Wang Dandan;Song Huaibo;He Dongjian;College of Mechanical and Electronic Engineering, Northwest A&F University;;Research advance on vision system of apple picking robot[J];农业工程学报;2017-10
5 LIU Shiwei;LV Jingnan;MO Lan;China Mobile Group Guangdong Co.,Ltd.,Dongguan Branch;;Research on an Novel Prediction Method Based on Customer Complaint Information[J];移动通信;2017-08
6 HOU Yuqingyang;QUAN Jicheng;WANG Hongwei;The Aviation University of Airforce;;Review of Deep Learning Development[J];舰船电子工程;2017-04
7 Chen Zhixuan;Zhou Dake;Huang Jingwei;Nanjing University of Aeronautics and Astronautics college of Automation;;Expression invariant 3D face recognition using convolutional neural networks[J];电子测量技术;2017-04
8 CHEN Zhi-wei;CHEN Shu;College of Information Engineering,Xiangtan University;;Automatic initialization of face tracking based on deep learning[J];计算机工程与科学;2017-04
9 MA Shilong;WUNIRI Qiqige;LI Xiaoping;State Key Laboratory of Software Development Environment, Beihang University;;Deep learning with big data:state of the art and development[J];智能系统学报;2016-06
【Secondary Citations】
Chinese Journal Full-text Database 7 Hits
1 NIE Ren-can;YAO Shao-wen;ZHOU Dong-ming;Information College,Yunnan University;Graduate College,Yunnan University;;Face Recognition Using Simplified Pulse Coupled Neural Network[J];计算机科学;2014-02
2 Yu Kai;Jia Lei;Chen Yuqiang;Xu Wei;Baidu;;Deep Learning:Yesterday,Today,and Tomorrow[J];计算机研究与发展;2013-09
3 ZHAO Yuan-qing1 WU hua2(School of Computer and Information Engineering,Anyang Normal University,Anyang 455000,China)1(Computer Teaching Department of Anyang Normal University,Anyang 455000,China)2;Handwritten Numeral Recognition Based on Multi-scale Features and Neural Network[J];计算机科学;2013-08
4 Sun Zhi-jun Xue Lei Xu Yang-ming(Electronic Engineering Institute,Hefei 230037,China)(Anhui Province Key Laboratory of Electronic Restriction,Hefei 230037,China);Marginal Fisher Feature Extraction Algorithm Based on Deep Learning[J];电子与信息学报;2013-04
5 LI Haifeng1,LI Chunguo2(1.Department of Academic Affairs,Hebei University,Baoding 071002,China; 2.College of Mathematics and Computer Science,Hebei University,Baoding 071002,China);Note on deep architecture and deep learning algorithms[J];河北大学学报(自然科学版);2012-05
6 SUN Zhi-jun 1,XUE Lei 1,2,XU Yang-ming 1,2,WANG Zheng 1,2(1.Electronic Engineering Institute,Hefei 230037,China;2.Key Laboratory of Electronic Restriction,Hefei 230037,China);Overview of deep learning[J];计算机应用研究;2012-08
7 Kong Bin Ph.D.Candidate, Associate Professor, Hefei Institute of Intelligent Machines, Chinese Academy of Sciences,Hefei 230031;Comparison Between Human Vision and Computer Vision[J];自然杂志;2002-01
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