Data-oriented composite-kernel-based support vector machine for image classification
文献类型：期刊论文
| 作者 | Jiakui Tang ; Xianfeng Zhang ; Xiuwan Chen ; Jie Zhang ; Xiaohu Wena ; Zhidong Zhang ; De Wang |
| 刊名 | Proc. of SPIE
 |
| 出版日期 | 2009 |
| 卷号 | 7471页码:74711X-1--74711X-9 |
| 关键词 | Support Vector Machine Composite Kernel Mage Classification Remote Sensing |
| 通讯作者 | Jiakui Tang |
| 英文摘要 | One novel composite kernel based support vector machine (SVM), which is called DOCKSVM (Data Oriented Composite Kernel based Support Vector Machine) is proposed in the paper. SVM have been proved good potential in various studies, and tried to application for pattern classification problems such as text categorization, image classification, objects detection etc. Recently, more and more researches show that SVM is promising in remote sensing image classification. Unlike traditional SVM method, DOCKSVM could integrate the bio-geophysical character into final classification through the composite kernels, which lead to the accuracy improvement of classification results. Firstly method of DOCKSVM is described in detail, then the novel method according to information entropy of training data to evaluate the weighted value of kernels is proposed, finally, preliminary results of application to remote sensing image classification is given which show that it’s good potential tool for remote sensing image classification. |
| 语种 | 英语 |
| 公开日期 | 2011-07-22 |
| 源URL | [http://ir.yic.ac.cn/handle/133337/4488]  |
| 专题 | 烟台海岸带研究所_科研共享资源 |
| 推荐引用方式 GB/T 7714 | Jiakui Tang,Xianfeng Zhang,Xiuwan Chen,et al. Data-oriented composite-kernel-based support vector machine for image classification[J]. Proc. of SPIE,2009,7471:74711X-1--74711X-9. |
| APA | Jiakui Tang.,Xianfeng Zhang.,Xiuwan Chen.,Jie Zhang.,Xiaohu Wena.,...&De Wang.(2009).Data-oriented composite-kernel-based support vector machine for image classification.Proc. of SPIE,7471,74711X-1--74711X-9. |
| MLA | Jiakui Tang,et al."Data-oriented composite-kernel-based support vector machine for image classification".Proc. of SPIE 7471(2009):74711X-1--74711X-9. |
入库方式： OAI收割
来源：烟台海岸带研究所
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