@inproceedings{ea4e0c52482143d88793a88f85dc5d0f,
title = "A vehicle detection using selective multi-stage features in convolutional neural networks",
abstract = "Vehicle detection is the most basic and important technology in advanced driver assistant system. Conventional methods do not reflect characteristic information of vehicle images, so they were vulnerable to noise. In order to improve the performance of vehicle detection, this paper proposes a vehicle detection framework using selective multi-stage features in convolutional neural networks. We design the convolutional neural network (CNN) model with 10 layers and use a visualization technique to selectively extract features from the activation feature map in CNN. Our proposed features have the characteristic information of vehicle images and are more robust to noise than traditional appearance based features. We train the Adaboost algorithm using these features to implement a vehicle detector. The result of the experiments proves that our proposed vehicle detection framework has a better performance than other frameworks.",
keywords = "Adaboost, Advanced driver assistant system, CNN, Vehicle detection",
author = "Lee, {Won Jae} and Pae, {Dong Sung} and Kim, {Dong Won} and Lim, {Myo Taeg}",
note = "Funding Information: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (Grant No. NRF-2016R1D1A1B01016071) Funding Information: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (Grant No. NRF-2016R1D1A1B01016071). Publisher Copyright: {\textcopyright} 2017 Institute of Control, Robotics and Systems - ICROS.; 17th International Conference on Control, Automation and Systems, ICCAS 2017 ; Conference date: 18-10-2017 Through 21-10-2017",
year = "2017",
month = dec,
day = "13",
doi = "10.23919/ICCAS.2017.8204413",
language = "English",
series = "International Conference on Control, Automation and Systems",
publisher = "IEEE Computer Society",
pages = "1--3",
booktitle = "ICCAS 2017 - 2017 17th International Conference on Control, Automation and Systems - Proceedings",
}