Proceedings of the 2016 International Conference on Education, Management and Computer Science

Rock Thin Section Image Classification Research from Shallow Network to Deep Neural Network

Authors
Rongfang Gao, Chunxu Ji, Xinjian Qiang, Guojian Cheng, Ye Liu
Corresponding Author
Rongfang Gao
Available Online May 2016.
DOI
https://doi.org/10.2991/icemc-16.2016.125How to use a DOI?
Keywords
Rock thin section image classification; Shallow network; BP neural network; Deep neural network; Convolutional neural network; Deep learning
Abstract
Image classification technology has made tremendous progress with the development from shallow network (neural network) to deep neural network, image classification based on deep neural network has become popular in the field of image classification technology. By introducing shallow network and deep neural network, and making classification for 30 rock thin section images and contrast according to connectivity of pores with examples of the BP neural network (hidden layer has 6 neuron nodes and 7 neuron nodes) from shallow network and the convolutional neural network from deep neural network, finally, the average error rate of classification for deep neural network is 0%, and the average error rate of classification for BP neural network are 24.666% and 19.334% respectively, which shows that rock thin section image classification based on deep neural network has higher efficiency and better classification result than rock thin section image classification based on shallow network.
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Proceedings
2016 International Conference on Education, Management and Computer Science
Part of series
Advances in Intelligent Systems Research
Publication Date
May 2016
ISBN
978-94-6252-202-2
ISSN
1951-6851
DOI
https://doi.org/10.2991/icemc-16.2016.125How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Rongfang Gao
AU  - Chunxu Ji
AU  - Xinjian Qiang
AU  - Guojian Cheng
AU  - Ye Liu
PY  - 2016/05
DA  - 2016/05
TI  - Rock Thin Section Image Classification Research from Shallow Network to Deep Neural Network
BT  - 2016 International Conference on Education, Management and Computer Science
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/icemc-16.2016.125
DO  - https://doi.org/10.2991/icemc-16.2016.125
ID  - Gao2016/05
ER  -