@article{ref1,
title="Vehicle type recognition using on-board sensor information integration by a multiple-structured neural network",
journal="Review of automotive engineering",
year="2005",
author="Zheng, Min and Gotoh, Tadao and Shimomura, N",
volume="26",
number="2",
pages="185-190",
abstract="In this paper, an algorithm for vehicle type recognition using on-board sensor information integration is proposed. In this method, frame recognition is firstly performed based on a multiple structured neural network using three kinds of sensing data, distance and reflective intensity data from a Scanning Laser Radar, and images taken by a CCD camera. Then, the results of recognition for sequential frames are integrated so as to improve the recognition accuracy of each object. Experimental results using driving road images and sensing data show this method is effective: average recognition rates were more than 96.5% for various driving and road conditions. 2005 Society of Automotive Engineers of Japan, Inc. All rights reserved.<p />",
language="",
issn="1349-4724",
doi="",
url="http://dx.doi.org/"
}