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《Journal of Changchun University of Technology》 2019-04
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Wood defect recognition based on convolutional neural network

CUI Mingguang;ZHANG Xiumei;HAN Weina;School of Electrical & Electronic Engineering, Changchun University of Technology;  
A cross-layer convolution neural network model is composed of input, two staggered convolution, pooling, full connection and output layers. The output of the two pooling layers are sent to the full connection layer for building the classifier with both high-level features and low-level features of the network. Dropout technology is added to the network for preventing over-fitting.
【Fund】: 国家自然科学基金资助项目(61374051)
【CateGory Index】: S781.5;TP391.41;TP183
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【Citations】
Chinese Journal Full-text Database 2 Hits
1 XU Shan-shan,LIU Ying-an,XU Sheng(College of Information Science and Technology,Nanjing Forestry University,Nanjing 210037,China);Wood defects recognition based on the convolutional neural network[J];山东大学学报(工学版);2013-02
2 Yang Huimin, Wang Lihai(Northeast Forestry University, Harbin 150040, P. R. China);Nondestructive Testing of Wood Hole Defect by Ultrasonic Spectrum Analysis[J];东北林业大学学报;2007-08
【Co-citations】
Chinese Journal Full-text Database 10 Hits
1 SONG Bo;WANG Qichun;;Application of Convolutional Neural Network in Identification of Guideboards[J];公路交通技术;2015-05
2 Hu Junfeng;Cao Jun;Zhao Yafeng;Northeast Forestry University;;Random Forest in Board Surface Defect Classification[J];东北林业大学学报;2015-08
3 Yang Huimin;Wang Lihai;Northeast Forest University;;Correlation and Influencing Factors between Wood Defect and Ultrasonic Propagation Parameters[J];东北林业大学学报;2015-08
4 XUE Haotian;YANG Jingdong;TAN Kaide;Department of Control Engineering,University of Shanghai for Science & Technology;;Application of an Improved BP Neural Network in Handwriting Recognition[J];电子科技;2015-05
5 CAI Juan;CAI Jian-Yong;LIAO Xiao-Dong;HUANG Hai-Tao;DING Qiao-Jun;School of Electronic College of Photonic and Electronic Engineering,Fujian Normal University;Key Laboratory of Optoelectronic Science and Technology for Medicine Ministry of Education,Fujian Normal University;Fujian Provincial Key Laboratory for Photonics Technology,Fujian Normal University;Intelligent Optoelectronic Systems Research Centre,Fujian Normal University;;Preliminary Study on Hand Gesture Recognition Based on Convolutional Neural Network[J];计算机系统应用;2015-04
6 JIN Shou-ling;DU Xiao-chen;FENG Hai-lin;FANG Yi-ming;WANG Zai-chao;School of Information Engineering, Zhejiang A & F University;Zhejiang Provincial Key Laboratory of Intelligent Monitoring in Forestry and Information Technology;Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory;;Effect of Moisture Content on Stress Wave Spectrum of Carya cathayensis Wood[J];浙江林业科技;2015-01
7 GE Ming-tao;WANG Xiao-li;PAN Li-wu;SIAS International School,Zhengzhou University;Henan University of Animal Husbandry and Economy;;Large pattern online handwriting character recognition based on multi-convolution neural network[J];现代电子技术;2014-20
8 Xu Huadong;Wang Lihai;Northeast Forestry University;;Effects of Cavity on Propagation Path of Stress Wave in Wood[J];东北林业大学学报;2014-04
9 Sun Jianping;Hu Yingcheng;Wang Fenghu;Key Laboratory of Bio-based Material Science and Technology of Ministry of Education,Northeast Forestry University;The College of Forestry,Guangxi University;;Study on quantitative nondestructive test of wood defects based on intelligent technology[J];仪器仪表学报;2013-09
10 XU Shan-shan,LIU Ying-an,XU Sheng(College of Information Science and Technology,Nanjing Forestry University,Nanjing 210037,China);Wood defects recognition based on the convolutional neural network[J];山东大学学报(工学版);2013-02
【Secondary Citations】
Chinese Journal Full-text Database 3 Hits
1 Yang Huimin, Wang Lihai(Northeast Forestry University, Harbin 150040, P. R. China);Nondestructive Testing of Wood Hole Defect by Ultrasonic Spectrum Analysis[J];东北林业大学学报;2007-08
2 Qi Wei Wang Lihai(Northeast Forestry University Harbin 150040);Identifying the Patterns of Defects in Timber Using Ultrasonic Test Based on Wavelet Neural Networks[J];林业科学;2006-08
3 WANG Lihai (Northeast Forestry University, Harbin 150040);Current Situaton of Research on the Non-Destructive Testing Technique for Wood Defects[J];林业科技;2002-03
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