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Semi-supervised Learning in Traffic Scene Surveillance Based on Label-propagation
Meng Liang; Zhaoxiang Zhang; Yunhong Wang
2013-09-15
会议名称International Conference on Image Processing
会议录名称ICIP 2013
会议日期15-18 September 2013
会议地点Melbourne, Australia
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.
关键词Semi-supervised Learning Traffic Scene Surveillance Object Classification Label Propagation
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/13287
专题类脑智能研究中心
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],2013.
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