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Research on Optimization Method of Deep Neural Network
Liu PF(刘鹏飞); Zhao HC(赵怀慈); Cao FD(曹飞道)
作者部门光电信息技术研究室
会议名称LIDAR IMAGING DETECTION AND TARGET RECOGNITION 2017
会议日期July 23-25, 2017
会议地点Changchun, China
会议主办者Chinese Society for Optical Engineering (CSOE)
会议录名称Proceedings SPIE 10605, LIDAR Imaging Detection and Target Recognition 2017
出版者SPIE
出版地Bellingham, USA
2017
页码1-6
收录类别EI ; CPCI(ISTP)
EI收录号20181705046915
WOS记录号WOS:000426279000096
产权排序1
ISSN号0277-786X
关键词Deep Neural Network Object Classification Over-fitting Loss Function
摘要Image recognition technology has been widely applied and played an important role in various fields nowadays. Because of multi-layer structure of deep network can use a more concise way to express complex functions, deep neural network (DNN) will be applied to the image recognition to improve the accuracy of image classification. Analysis the existing problems of deep neural network. Then put forward new approaches to solve the gradient vanishing and over-fitting problems. The experimental results which verified on the MNIST, show that our proposed approaches can improve the classification accuracy greatly and accelerate the convergence speed. Compared to support vector machine (SVM), the optimized model of the neural network is not only effective, but also converged quickly.
语种英语
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文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/21306
专题光电信息技术研究室
通讯作者Zhao HC(赵怀慈)
作者单位1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016
2.University of Chinese Academy of Sciences, Beijing 100049
3.Key Laboratory of Opto-Electronic Information Processing, CAS, Shenyang 110016
4.The Key Lab of Image Understanding and Computer Vision, Liaoning Province, Shenyang 110016
推荐引用方式
GB/T 7714
Liu PF,Zhao HC,Cao FD. Research on Optimization Method of Deep Neural Network[C]//Chinese Society for Optical Engineering (CSOE). Bellingham, USA:SPIE,2017:1-6.
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