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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
Conference Name2018 International Conference on Electronics Technology, ICET 2018
Source Publication2018 International Conference on Electronics Technology, ICET 2018
Pages345-348
Conference Date2018-05-23
Conference PlaceChengdu, China
PublisherInstitute of Electrical and Electronics Engineers Inc.
Contribution Rank1
AbstractWith 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.
Department光电测量技术实验室
DOI10.1109/ELTECH.2018.8401481
Indexed ByEI
ISBN9781538657522
Language英语
EI Accession Number20183105630584
Citation statistics
Document Type会议论文
Identifierhttp://ir.opt.ac.cn/handle/181661/30548
Collection光电测量技术实验室
Affiliation1.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
Recommended Citation
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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