Image Classification Based on Convolutional Denoising Sparse Autoencoder
Joint Authors
Zeng, Xiaoqin
Chen, Shuangshuang
Liu, Huiyi
Qian, Subin
Yu, Jianjiang
Guo, Wei
Source
Mathematical Problems in Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-11-26
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
Image classification aims to group images into corresponding semantic categories.
Due to the difficulties of interclass similarity and intraclass variability, it is a challenging issue in computer vision.
In this paper, an unsupervised feature learning approach called convolutional denoising sparse autoencoder (CDSAE) is proposed based on the theory of visual attention mechanism and deep learning methods.
Firstly, saliency detection method is utilized to get training samples for unsupervised feature learning.
Next, these samples are sent to the denoising sparse autoencoder (DSAE), followed by convolutional layer and local contrast normalization layer.
Generally, prior in a specific task is helpful for the task solution.
Therefore, a new pooling strategy—spatial pyramid pooling (SPP) fused with center-bias prior—is introduced into our approach.
Experimental results on the common two image datasets (STL-10 and CIFAR-10) demonstrate that our approach is effective in image classification.
They also demonstrate that none of these three components: local contrast normalization, SPP fused with center-prior, and l2 vector normalization can be excluded from our proposed approach.
They jointly improve image representation and classification performance.
American Psychological Association (APA)
Chen, Shuangshuang& Liu, Huiyi& Zeng, Xiaoqin& Qian, Subin& Yu, Jianjiang& Guo, Wei. 2017. Image Classification Based on Convolutional Denoising Sparse Autoencoder. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-16.
https://search.emarefa.net/detail/BIM-1190670
Modern Language Association (MLA)
Chen, Shuangshuang…[et al.]. Image Classification Based on Convolutional Denoising Sparse Autoencoder. Mathematical Problems in Engineering No. 2017 (2017), pp.1-16.
https://search.emarefa.net/detail/BIM-1190670
American Medical Association (AMA)
Chen, Shuangshuang& Liu, Huiyi& Zeng, Xiaoqin& Qian, Subin& Yu, Jianjiang& Guo, Wei. Image Classification Based on Convolutional Denoising Sparse Autoencoder. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-16.
https://search.emarefa.net/detail/BIM-1190670
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1190670