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Research on optimization method of convolutional nerual network
Feng, Xubin1,2; Su, Xiuqin1; Yan, Minqi1; Xie, Meilin1; Liu, Peng1; Lian, Xuezheng1; Jing, Feng1
2018-06-29
会议名称2018 International Conference on Electronics Technology, ICET 2018
会议录名称2018 International Conference on Electronics Technology, ICET 2018
页码345-348
会议日期2018-05-23
会议地点Chengdu, China
出版者Institute of Electrical and Electronics Engineers Inc.
产权排序1
摘要With the improvement of computers' computation and storage performance, the deep learning technology, especially the convolutional neural network (CNN) has been widely used in many fields such as Computer Vision (CV), Natural Language Processing (NLP) and Automatic Speech Recognition (ASR). CNNs have become the state-of-The-Art technique in many vision tasks, such as image classification, object detection, etc. But the deep CNNs may make part of the kernels too thin by using parameterized convolution kernel to extract features. Therefore, this paper proposes a method to optimize CNNs by calculating the similarity coefficient between the feature maps. Experimental results showed that this method improved the training speed and the detecting speed with the accuracy been ensured. © 2018 IEEE.
作者部门光电测量技术实验室
DOI10.1109/ELTECH.2018.8401481
收录类别EI
ISBN号9781538657522
语种英语
EI入藏号20183105630584
引用统计
文献类型会议论文
条目标识符http://ir.opt.ac.cn/handle/181661/30548
专题光电测量技术实验室
作者单位1.Photoelectric Tracking, Xi'An Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China;
2.University of Chinese Academy of Sciences, China
推荐引用方式
GB/T 7714
Feng, Xubin,Su, Xiuqin,Yan, Minqi,et al. Research on optimization method of convolutional nerual network[C]:Institute of Electrical and Electronics Engineers Inc.,2018:345-348.
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