Vehicle Make and Model Recognition Based on Convolutional Neural Networks

被引：0

作者：

Ren, Yongguo ^{[1
]}

Lan, Shanzhen ^{[2
]}

机构：

[1] Commun Univ China, Dept Network Engn, Beijing 100024, Peoples R China

[2] Commun Univ China, Dept Digital Media Technol, Beijing 100024, Peoples R China

来源：

PROCEEDINGS OF 2016 IEEE 7TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND SERVICE SCIENCE (ICSESS 2016) | 2016年

关键词：

moving vehicle detection; vehicle make and model recognition; deep learning; pattern recognition;

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Vehicle analysis is an important task in many intelligent applications, which involves vehicle-type classification(VTC), license-plate recognition(LPR) and vehicle make and model recognition(MMR). Among these tasks, MMR plays an important complementary role with respect to LPR. In this paper, we propose a novel framework to detect moving vehicle and MMR using convolutional neural networks. The frontal view of vehicle images first extracted and fed into convolutional neural networks for training and testing. The experimental results show that our proposed framework achieves favorable recognition accuracy 98.7% in terms of our vehicle MMR.

引用

页码：692 / 695

页数：4

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