Study on image classification with convolution neural networks

Lei Wang; Yanning Zhang; Runping Xi

doi:10.1007/978-3-319-23989-7_32

Study on image classification with convolution neural networks

Lei Wang, Yanning Zhang, Runping Xi

School of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Classification is one of the most popular topics in image process. In this paper, it provides the specific process of convolutional neural network in deep learning. Here builds typical convolution neural network which parameters and the connection mode can be adjusted. In addition, we present our preliminary classification results. Through the experiments of a convolutional neural network on the Mixed National Institute of Standards and Technology database (MNIST), we compared with the classification results and analyzed in the experimental results with the parameters. The experimental results show that image classification effect is very good used by convolutional neural network.

Original language	English
Title of host publication	Intelligence Science and Big Data Engineering
Subtitle of host publication	Image and Video Data Engineering - 5th International Conference, IScIDE 2015, Revised Selected Papers
Editors	Xiaofei He, Zhi-Hua Zhou, Xinbo Gao, Zhi-Yong Liu, Yanning Zhang, Baochuan Fu, Fuyuan Hu, Zhancheng Zhang
Publisher	Springer Verlag
Pages	310-319
Number of pages	10
ISBN (Print)	9783319239873
DOIs	https://doi.org/10.1007/978-3-319-23989-7_32
State	Published - 2015
Event	5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015 - Suzhou, China Duration: 14 Jun 2015 → 16 Jun 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9242
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015
Country/Territory	China
City	Suzhou
Period	14/06/15 → 16/06/15

Keywords

Convolutional Neural Networks (CCN)
Deep learning
Handwritten digits
Image classification

Access to Document

10.1007/978-3-319-23989-7_32

Cite this

Wang, L., Zhang, Y., & Xi, R. (2015). Study on image classification with convolution neural networks. In X. He, Z.-H. Zhou, X. Gao, Z.-Y. Liu, Y. Zhang, B. Fu, F. Hu, & Z. Zhang (Eds.), Intelligence Science and Big Data Engineering: Image and Video Data Engineering - 5th International Conference, IScIDE 2015, Revised Selected Papers (pp. 310-319). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9242). Springer Verlag. https://doi.org/10.1007/978-3-319-23989-7_32

Wang, Lei ; Zhang, Yanning ; Xi, Runping. / Study on image classification with convolution neural networks. Intelligence Science and Big Data Engineering: Image and Video Data Engineering - 5th International Conference, IScIDE 2015, Revised Selected Papers. editor / Xiaofei He ; Zhi-Hua Zhou ; Xinbo Gao ; Zhi-Yong Liu ; Yanning Zhang ; Baochuan Fu ; Fuyuan Hu ; Zhancheng Zhang. Springer Verlag, 2015. pp. 310-319 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{7664d7f1380146e09ec0a297f8ab26b5,

title = "Study on image classification with convolution neural networks",

abstract = "Classification is one of the most popular topics in image process. In this paper, it provides the specific process of convolutional neural network in deep learning. Here builds typical convolution neural network which parameters and the connection mode can be adjusted. In addition, we present our preliminary classification results. Through the experiments of a convolutional neural network on the Mixed National Institute of Standards and Technology database (MNIST), we compared with the classification results and analyzed in the experimental results with the parameters. The experimental results show that image classification effect is very good used by convolutional neural network.",

keywords = "Convolutional Neural Networks (CCN), Deep learning, Handwritten digits, Image classification",

author = "Lei Wang and Yanning Zhang and Runping Xi",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015 ; Conference date: 14-06-2015 Through 16-06-2015",

year = "2015",

doi = "10.1007/978-3-319-23989-7_32",

language = "英语",

isbn = "9783319239873",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "310--319",

editor = "Xiaofei He and Zhi-Hua Zhou and Xinbo Gao and Zhi-Yong Liu and Yanning Zhang and Baochuan Fu and Fuyuan Hu and Zhancheng Zhang",

booktitle = "Intelligence Science and Big Data Engineering",

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Wang, L, Zhang, Y & Xi, R 2015, Study on image classification with convolution neural networks. in X He, Z-H Zhou, X Gao, Z-Y Liu, Y Zhang, B Fu, F Hu & Z Zhang (eds), Intelligence Science and Big Data Engineering: Image and Video Data Engineering - 5th International Conference, IScIDE 2015, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9242, Springer Verlag, pp. 310-319, 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015, Suzhou, China, 14/06/15. https://doi.org/10.1007/978-3-319-23989-7_32

Study on image classification with convolution neural networks. / Wang, Lei; Zhang, Yanning; Xi, Runping.
Intelligence Science and Big Data Engineering: Image and Video Data Engineering - 5th International Conference, IScIDE 2015, Revised Selected Papers. ed. / Xiaofei He; Zhi-Hua Zhou; Xinbo Gao; Zhi-Yong Liu; Yanning Zhang; Baochuan Fu; Fuyuan Hu; Zhancheng Zhang. Springer Verlag, 2015. p. 310-319 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9242).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Study on image classification with convolution neural networks

AU - Wang, Lei

AU - Zhang, Yanning

AU - Xi, Runping

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2015.

PY - 2015

Y1 - 2015

N2 - Classification is one of the most popular topics in image process. In this paper, it provides the specific process of convolutional neural network in deep learning. Here builds typical convolution neural network which parameters and the connection mode can be adjusted. In addition, we present our preliminary classification results. Through the experiments of a convolutional neural network on the Mixed National Institute of Standards and Technology database (MNIST), we compared with the classification results and analyzed in the experimental results with the parameters. The experimental results show that image classification effect is very good used by convolutional neural network.

AB - Classification is one of the most popular topics in image process. In this paper, it provides the specific process of convolutional neural network in deep learning. Here builds typical convolution neural network which parameters and the connection mode can be adjusted. In addition, we present our preliminary classification results. Through the experiments of a convolutional neural network on the Mixed National Institute of Standards and Technology database (MNIST), we compared with the classification results and analyzed in the experimental results with the parameters. The experimental results show that image classification effect is very good used by convolutional neural network.

KW - Convolutional Neural Networks (CCN)

KW - Deep learning

KW - Handwritten digits

KW - Image classification

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U2 - 10.1007/978-3-319-23989-7_32

DO - 10.1007/978-3-319-23989-7_32

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SN - 9783319239873

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 310

EP - 319

BT - Intelligence Science and Big Data Engineering

A2 - He, Xiaofei

A2 - Zhou, Zhi-Hua

A2 - Gao, Xinbo

A2 - Liu, Zhi-Yong

A2 - Zhang, Yanning

A2 - Fu, Baochuan

A2 - Hu, Fuyuan

A2 - Zhang, Zhancheng

PB - Springer Verlag

T2 - 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015

Y2 - 14 June 2015 through 16 June 2015

ER -

Wang L, Zhang Y, Xi R. Study on image classification with convolution neural networks. In He X, Zhou ZH, Gao X, Liu ZY, Zhang Y, Fu B, Hu F, Zhang Z, editors, Intelligence Science and Big Data Engineering: Image and Video Data Engineering - 5th International Conference, IScIDE 2015, Revised Selected Papers. Springer Verlag. 2015. p. 310-319. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-23989-7_32

Study on image classification with convolution neural networks

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