@inproceedings{f0acd999bd844a998bc6419bd5516e9f,
title = "Parking Space Recognition Methods Based on Visual Image and Deep Learning",
abstract = "Parking space recognition technology is of great significance for intelligent parking lot management. To address the shortcomings of current parking lot management methods, we conducted research and practice on parking space recognition based on image processing and deep learning methods, resulting in a comprehensive and effective parking space recognition method. By preprocessing the parking lot images to divide the parking area and using the VGG16 neural network for parking space recognition training, we processed the parking lot video with the trained model. The experimental results show that most of the parking spaces in the video can be accurately identified, with an accuracy rate of 98.32\%. The link to the parking space recognition video is: https://youtu.be/9xMph9USgW4.",
keywords = "Deep Learning, Image Processing, Parking Space Recognition, VGG16",
author = "Siyi Deng and Yuchen Xia and Weiliang Zuo and Jingmin Xin and Sanping Zhou and Nanning Zheng",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 China Automation Congress, CAC 2023 ; Conference date: 17-11-2023 Through 19-11-2023",
year = "2023",
doi = "10.1109/CAC59555.2023.10451942",
language = "英语",
series = "Proceedings - 2023 China Automation Congress, CAC 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "6677--6682",
booktitle = "Proceedings - 2023 China Automation Congress, CAC 2023",
}