Image generation classification method based on convolution neural network

Using convolution neural network which though convolution and pooling extracting features of high dis-tinguish ability and then make fusion for classification of natural images and scanned documents.Experimental re-sults show that the classification accuracy of the proposed classification method is...

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Main Authors: Qiao-ling LI, Qing-xiao GUAN, Xian-feng ZHAO
Format: Article
Language:English
Published: POSTS&TELECOM PRESS Co., LTD 2016-09-01
Series:网络与信息安全学报
Subjects:
Online Access:http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2016.00096
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author Qiao-ling LI
Qing-xiao GUAN
Xian-feng ZHAO
author_facet Qiao-ling LI
Qing-xiao GUAN
Xian-feng ZHAO
author_sort Qiao-ling LI
collection DOAJ
description Using convolution neural network which though convolution and pooling extracting features of high dis-tinguish ability and then make fusion for classification of natural images and scanned documents.Experimental re-sults show that the classification accuracy of the proposed classification method is more than 93% on the SKL image database.The model is highly robust to font sizes and image formats.Through contrast experiment validated that preprocessing of image has a positive effect on the accuracy of the model and the time cost on training.
format Article
id doaj-art-591c33ef1aa1452a83ee16d6e6a6acb1
institution Kabale University
issn 2096-109X
language English
publishDate 2016-09-01
publisher POSTS&TELECOM PRESS Co., LTD
record_format Article
series 网络与信息安全学报
spelling doaj-art-591c33ef1aa1452a83ee16d6e6a6acb12025-01-15T03:04:52ZengPOSTS&TELECOM PRESS Co., LTD网络与信息安全学报2096-109X2016-09-012404859548006Image generation classification method based on convolution neural networkQiao-ling LIQing-xiao GUANXian-feng ZHAOUsing convolution neural network which though convolution and pooling extracting features of high dis-tinguish ability and then make fusion for classification of natural images and scanned documents.Experimental re-sults show that the classification accuracy of the proposed classification method is more than 93% on the SKL image database.The model is highly robust to font sizes and image formats.Through contrast experiment validated that preprocessing of image has a positive effect on the accuracy of the model and the time cost on training.http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2016.00096convolution neural networkimage generation modecontent pattern classificationmultimedia security
spellingShingle Qiao-ling LI
Qing-xiao GUAN
Xian-feng ZHAO
Image generation classification method based on convolution neural network
网络与信息安全学报
convolution neural network
image generation mode
content pattern classification
multimedia security
title Image generation classification method based on convolution neural network
title_full Image generation classification method based on convolution neural network
title_fullStr Image generation classification method based on convolution neural network
title_full_unstemmed Image generation classification method based on convolution neural network
title_short Image generation classification method based on convolution neural network
title_sort image generation classification method based on convolution neural network
topic convolution neural network
image generation mode
content pattern classification
multimedia security
url http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2016.00096
work_keys_str_mv AT qiaolingli imagegenerationclassificationmethodbasedonconvolutionneuralnetwork
AT qingxiaoguan imagegenerationclassificationmethodbasedonconvolutionneuralnetwork
AT xianfengzhao imagegenerationclassificationmethodbasedonconvolutionneuralnetwork