SEMI-SUPERVISED SPECTRAL CLUSTERING ENSEMBLE FOR TRAFFIC SIGN CATEGORIZATION

被引：0
|
作者：
Yan, Shan [1 ]
Wang, Hongjun [1 ]
Guo, Jin [1 ]
Li, Tianrui [1 ]
机构：
[1] Southwest Jiaotong Univ, Sch Informat Sci & Technol, Chengdu 611756, Sichuan, Peoples R China
来源：
UNCERTAINTY MODELLING IN KNOWLEDGE ENGINEERING AND DECISION MAKING | 2016年 / 10卷
关键词：
Clustering Ensemble; Semi-supervised Spectral Clustering Ensemble; Traffic Sign Categorization;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Traffic sign recognition is a significant part in advanced driving assistance system. In this paper, a semi-supervised spectral cluster ensemble model is designed for traffic sign recognition, and the spectral model is based on pairwise constraints. Then, the inference of the proposed model is illustrated in detail and the corresponding algorithm is stated step by step. At last, real datasets are selected for experiment and the experimental results show that the proposed algorithm can work well.
引用
收藏
页码：368 / 376
页数：9
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