Image Classification Based on Sparse Autoencoder and Support Vector Machine

Authors

Liu Fang, College of Information and Communication Engineering, Beijing University of Technology, Beijing 100124, China;
Lixia Lu, College of Information and Communication Engineering, Beijing University of Technology, Beijing 100124, China;
Hongjuan Wang, College of Information and Communication Engineering, Beijing University of Technology, Beijing 100124, China;
Wang Xin, College of Information and Communication Engineering, Beijing University of Technology, Beijing 100124, China;

Abstract

Abstract: A new algorithm of image classification based on the sparse autoencoder and the support vector machine was proposed in view of the drawbacks that the single layer sparse autoencoder for feature learning is easy to lose the deep abstract feature and the features lack the robustness. The deep sparse autoencoder is constructed to learn each image layer and the feature of each layer is automatically extracted. The each feature weights and the reorganized set of feature are obtained according to the feature weighting method. By combining the strong global search ability of genetic algorithm and the excellent performance of support vector machine, the image classification is completed efficiently and accurately. The experimental results show that the proposed algorithm can automatically learn the deep feature of the image, and the reorganized feature has high feature discrimination ability, which effectively improves the accuracy of image classification.

Recommended Citation

Fang, Liu; Lu, Lixia; Wang, Hongjuan; and Xin, Wang (2019) "Image Classification Based on Sparse Autoencoder and Support Vector Machine," Journal of System Simulation: Vol. 30: Iss. 8, Article 23.
DOI: 10.16182/j.issn1004731x.joss.201808023
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss8/23

First Page

3007

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201808023

Last Page

3014

CLC

TP391.41

Recommended Citation

Liu Fang, Lu Lixia, Wang Hongjuan, Wang Xin. Image Classification Based on Sparse Autoencoder and Support Vector Machine[J]. Journal of System Simulation, 2018, 30(8): 3007-3014.

DOI

10.16182/j.issn1004731x.joss.201808023