Multiview Canonical Correlation Analysis Networks for Remote Sensing Image Recognition
文献类型：期刊论文
| 作者 | Xinghao Yang; Weifeng Liu; Dapeng Tao; Jun Cheng; Shuying Li |
| 刊名 | IEEE Geoscience and Remote Sensing Letters
 |
| 出版日期 | 2017 |
| 文献子类 | 期刊论文 |
| 英文摘要 | In the past decade, deep learning (DL) algorithms have been widely used for remote sensing (RS) image recognition tasks. As the most typical DL model, convolutional neural networks (CNNs) achieves outstand performance for big RS data classification. Recently, a variant of CNN, dubbed canonical correlation analysis network (CCANet), was proposed to abstract the two-view image features. Extensive experiments conducted on several benchmark databases validate the effectiveness of CCANet. However, the CCANet structure is powerless when the observations arrive from more than two sources. To serve the multiview purpose, in this letter, we propose multiview CCANets (MCCANets). Particularly, the MCCANet model learns the stacked multiperspective filter banks by the MCCA method and builds a deep convolutional structure. In the output stage, the binarization and the blockwise histogram are employed as nonlinear processing and feature pooling, respectively. To access the effectiveness of the MCCANet, we conduct a host of experiments on the RSSCN7 RS database. Extensive experimental results demonstrate that the MCCANet outperforms the two-view CCANet. |
| URL标识 | 查看原文 |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/11648]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | IEEE Geoscience and Remote Sensing Letters |
| 推荐引用方式 GB/T 7714 | Xinghao Yang,Weifeng Liu,Dapeng Tao,et al. Multiview Canonical Correlation Analysis Networks for Remote Sensing Image Recognition[J]. IEEE Geoscience and Remote Sensing Letters,2017. |
| APA | Xinghao Yang,Weifeng Liu,Dapeng Tao,Jun Cheng,&Shuying Li.(2017).Multiview Canonical Correlation Analysis Networks for Remote Sensing Image Recognition.IEEE Geoscience and Remote Sensing Letters. |
| MLA | Xinghao Yang,et al."Multiview Canonical Correlation Analysis Networks for Remote Sensing Image Recognition".IEEE Geoscience and Remote Sensing Letters (2017). |
入库方式： OAI收割
来源：深圳先进技术研究院
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。