Road Vehicle Classification Based on Extreme Learning Machine

被引：0

作者：

Hao, Yan-shuang ^{[1
]}

Yin, Yi-xin ^{[1
]}

Lan, Jin-hui ^{[1
]}

机构：

[1] Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China

来源：

PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON ELECTRIC AND ELECTRONICS | 2013年

关键词：

Vehicle classification; Extreme learning machine; Invariant moments; Edge detection; EDGE;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

Road vehicle classification plays an important role in traffic surveillance, traffic security, and transportation management systems. This paper proposes a novel vehicle classification algorithm based on extreme learning machine. Invariant moments and horizontal edge features are extracted to classify vehicles into sedan, bus and van truck. Experimental results show that the proposed method can satisfactorily achieve vehicle classification at very fast training speed.

引用

页码：430 / 433

页数：4

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