@article{ref1,
title="Vehicle classification based on images from visible light and thermal cameras",
journal="EURASIP journal on image and video processing",
year="2018",
author="Nam, Yunyoung and Nam, Yun-Cheol",
volume="2018",
number="1",
pages="e5-e5",
abstract="The number of automobiles recently increased. The traffic level has also increased, leading to congestion and traffic accidents. A traffic accident has been a major challenge. Numerous machine-learning models have been developed to solve this challenge, and the existing system involves the use of hardware [11]. This model identifies the make of the car in the case of an auto-crash situation. Some autocrashes are hit-and-run, involving parked vehicles, and some would be a vehicle hitting pedestrians, cyclists, and motorcyclists. Convolutional neural networks (CNNs) are used in this model to predict cars. The convolutional neural networks (CNN) will aid in identifying and recognizing the make of the automobile.<p /> <p>Language: en</p>",
language="en",
issn="1687-5176",
doi="10.1186/s13640-018-0245-2",
url="http://dx.doi.org/10.1186/s13640-018-0245-2"
}