Laplacian Regularized Active Learning for Image Segmentation
文献类型：会议论文
| 作者 | Zhang, Lianbo; Tao, Dapeng; Liu, Weifeng |
| 出版日期 | 2014 |
| 会议名称 | Security, Pattern Analysis, and Cybernetics (SPAC), 2014 International Conference on |
| 会议地点 | 中国 |
| 英文摘要 | Image segmentation is a common topic in image processing. Many methods has been used in image segmentation, such as Graph cut, threshold-based. However, these methods can't work with high precision. Among these method, SVM is used as a good tool for classification, as we treat image segmentation as a problem of classification. To solve the problem above and get better segmentation result as well as high precision, we add Laplacian regularization to SVM algorithm to get a new algorithm i.e. Laplacian regularized active learning for image segmentation. Our algorithm considers distance between pixels when segmenting a picture, which is executed by Laplacian regularization. Experiments demonstrate that our algorithm perform better in comparison with common SVM algorithm |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/5595]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | 2014 |
| 推荐引用方式 GB/T 7714 | Zhang, Lianbo,Tao, Dapeng,Liu, Weifeng. Laplacian Regularized Active Learning for Image Segmentation[C]. 见:Security, Pattern Analysis, and Cybernetics (SPAC), 2014 International Conference on. 中国. |
入库方式： OAI收割
来源：深圳先进技术研究院
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