Semi-supervised Learning in Traffic Scene Surveillance Based on Label-propagation
文献类型：会议论文
| 作者 | Meng Liang; Zhaoxiang Zhang ; Yunhong Wang
|
| 出版日期 | 2013-09-15 |
| 会议日期 | 15-18 September 2013 |
| 会议地点 | Melbourne, Australia |
| 关键词 | Semi-supervised Learning Traffic Scene Surveillance Object Classification Label Propagation |
| 英文摘要 | Object classification in traffic scene surveillance has attracted much attention recent years. Traditional classification methods need lots of labeled samples to build a satisfying classifier. However, the acquisition of the labeled samples may cost lots of time and human labor. In this paper, we propose an label-propagation based semi-supervised learning method which uses the information of both labeled and un-labeled samples. Experiment results show that our method outperforms the traditional methods both in accuracy and robustness. |
| 会议录 | ICIP 2013
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/13287]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 通讯作者 | Zhaoxiang Zhang |
| 推荐引用方式 GB/T 7714 | Meng Liang,Zhaoxiang Zhang,Yunhong Wang. Semi-supervised Learning in Traffic Scene Surveillance Based on Label-propagation[C]. 见:. Melbourne, Australia. 15-18 September 2013. |
入库方式： OAI收割
来源：自动化研究所
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