Canonical correlation analysis networks for two-view image recognition.
文献类型：期刊论文
| 作者 | Yang, Xinghao; Liu, Weifeng; Tao, Dapeng; Cheng, Jun |
| 刊名 | INFORMATION SCIENCES
 |
| 出版日期 | 2017 |
| 文献子类 | 期刊论文 |
| 英文摘要 | In recent years, deep learning has attracted an increasing amount of attention in machine learning and artificial intelligence areas. Currently, many deep learning network-related architectures such as deep neural networks (DNNs), convolutional neural network (CNN), wavelet scattering network (ScatNet) and principal component analysis network (PCANet) have been proposed. The most effective network is PCANet, which has achieved promising performance in image classification, such as for face, object and handwritten digit recognition. PCANet can only handle data that are represented by single-view features. In this paper, we present a canonical correlation analysis network (CCANet) to address image classification, in which images are represented by two-viewfeatures. The CCANet learns two-view multistage filter banks by a canonical correlation analysis (CCA) method and constructs a cascaded convolutional deep network. Then, we incorporate filters with binaryzation and block-wise histogram processes to form the final depth structure. In addition, we introduce a variation of CCANet dubbed RandNet-2-in which the filter banks are randomly generated. Extensive experiments are conducted using the ETH-80, Yale-B, and USPS databases for object classification, face classification and handwritten digits classification, respectively. The experimental results demonstrate that the CCANet algorithm is more effective than PCANet, RandNet-1 and RandNet-2. |
| URL标识 | 查看原文 |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/11636]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | INFORMATION SCIENCES |
| 推荐引用方式 GB/T 7714 | Yang, Xinghao,Liu, Weifeng,Tao, Dapeng,et al. Canonical correlation analysis networks for two-view image recognition.[J]. INFORMATION SCIENCES,2017. |
| APA | Yang, Xinghao,Liu, Weifeng,Tao, Dapeng,&Cheng, Jun.(2017).Canonical correlation analysis networks for two-view image recognition..INFORMATION SCIENCES. |
| MLA | Yang, Xinghao,et al."Canonical correlation analysis networks for two-view image recognition.".INFORMATION SCIENCES (2017). |
入库方式： OAI收割
来源：深圳先进技术研究院
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