EIoU: An Improved Vehicle Detection Algorithm Based on VehicleNet Neural Network. Issue 1 (May 2021)

• Record Type: Journal Article
• Authors: Yang, Zuomin; Wang, Xianlun; Li, Jianguang
• Is Part Of: Journal of physics. Volume 1924:Issue 1(2021)
• Publication Date: 2021-05
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1924/1/012001
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: The paper's primary purpose is to optimize the performance (speed/accuracy) of vehicle detection. The vehicle dataset Vehicle2020 used in this paper is divided into ten different vehicle classes. Intersection over Union ( IoU ) is usually used as a standard to evaluate the accuracy of vehicle detection in a specific dataset. However, IoU as a performance of the object detection algorithm is still shortcomings. IoU is further improved and called a new algorithm EIoU . Finally, the neural network structure was redesigned, which was called VehicleNet. The experimental results show that EIoU as a performance evaluation algorithm used the vehicle detection framework can improve the performance of vehicle detection. Using the algorithm of this paper shows the performance superiority of vehicle detection.