@inproceedings{4883aea2ce9a4ead98482792c4057ab9,
title = "Vehicle detection in hsuehshan tunnel using background subtraction and deep belief network",
abstract = "This paper proposes a method to detect vehicle in the Hsuehshan Tunnel. Vehicle detection in the Tunnel is a challenging problem due to use of heterogeneous cameras, varied camera setup locations, low resolution videos, poor tunnel illumination, and reflected lights on the tunnel wall. Furthermore, the vehicles to be detected vary greatly in shape, color, size, and appearance. The proposed method is based on background subtraction and Deep Belief Network (DBN) with three hidden layers architecture. Experimental results show that it can detect vehicles in he Tunnel effectively. The experimental accuracy rate is 96.59%.",
keywords = "Background subtraction, Deep belief network, Long tunnel, Vehicle detection",
author = "Huang, {Bo Jhen} and Jun-Wei Hsieh and Tsai, {Chun Ming}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 9th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2017 ; Conference date: 03-04-2017 Through 05-04-2017",
year = "2017",
doi = "10.1007/978-3-319-54430-4_21",
language = "English",
isbn = "9783319544298",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "217--226",
editor = "Satoshi Tojo and Nguyen, {Le Minh} and Nguyen, {Ngoc Thanh} and Bogdan Trawinski",
booktitle = "Intelligent Information and Database Systems - 9th Asian Conference, ACIIDS 2017, Proceedings",
address = "德國",
}