Research on vehicle recognition based on deep learning

Ying Luo; Zhiquan Luo; Zhuoqian Liang

doi:10.1117/12.2674558

23 May 2023 Research on vehicle recognition based on deep learning

Ying Luo, Zhiquan Luo, Zhuoqian Liang

Proceedings Volume 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022); 126043H (2023) https://doi.org/10.1117/12.2674558
Event: 2nd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 2022, Guangzhou, China

Abstract

The increasing number of car ownership aggravates the traffic problem, so the intelligent transportation system is proposed. As a component of intelligent transportation system, vehicle identification system has been studied by researchers all over the world. In this paper, the theoretical knowledge of deep learning is introduced at first, and then the migration training is carried out by using VGG-16, RESNET-50 and the improved neural network based on these two kinds of networks on the self-made model dataset. In the experiment, a verification set was used to verify the training effect, and the training results of the four models were compared in terms of the number of parameters, training time and accuracy. The training results show that the improved RESNET-50 has the best performance, and its accuracy rate reaches 93%.

Citation Download Citation

Ying Luo, Zhiquan Luo, and Zhuoqian Liang "Research on vehicle recognition based on deep learning", Proc. SPIE 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 126043H (23 May 2023); https://doi.org/10.1117/12.2674558

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available