Change detection based on auto-encoder model for VHR images
文献类型：会议论文
| 作者 | Xu Y(徐元) ; Xiang Shiming; Huo Chunlei; Pan Chunhong; Xu Yuan
|
| 出版日期 | 2013 |
| 会议日期 | 2013-8-10 |
| 会议地点 | 武汉 |
| 关键词 | Change Detection Deep Learning Auto-encoder Vhr |
| 英文摘要 | Change detection of VHR (Very High Resolution) images is very difficult due to the impacts caused by the seasonal changes, the imaging condition, and so on. To address the above difficulty, a novel unsupervised change detection algorithm is proposed based on deep learning, where the complex correspondence between the images is established by Auto-encoder Model. By taking advantages of the powerful ability of deep learning in compensating the impacts implicitly, the multi-temporal images can be compared fairly. Experiments demonstrate the effectiveness of the proposed approach. |
| 会议录 | MIPPR2013
 |
| 会议录出版者 | International Society for Optics and Photonics |
| 会议录出版地 | 中国 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/11690]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_遥感图像处理团队 |
| 通讯作者 | Xu Yuan |
| 作者单位 | 中国科学院自动化研究所 |
| 推荐引用方式 GB/T 7714 | Xu Y,Xiang Shiming,Huo Chunlei,et al. Change detection based on auto-encoder model for VHR images[C]. 见:. 武汉. 2013-8-10. |
入库方式： OAI收割
来源：自动化研究所
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