Real-time vehicle detection algorithm based on a lightweight You-Only-Look-Once (YOLOv5n-L) approach

doi:10.1016/j.eswa.2022.119108

CIOMP OpenIR

	Real-time vehicle detection algorithm based on a lightweight You-Only-Look-Once (YOLOv5n-L) approach
	M. L. Bie; Y. Y. Liu; G. N. Li; J. T. Hong and J. Li
	2023
发表期刊	Expert Systems with Applications
ISSN	0957-4174
卷号	213 页码:9
摘要	A vehicle detection algorithm is of great significance for automatic driving technology. Current vehicle detection algorithms suffer from the complex structure, high configuration of hardware requirements, and the difficulty to apply to mobile terminal equipment. In order to solve these issues, this paper proposes an improved YOLOv5 algorithm, named YOLOv5n-L, for lightweight. First, a depthwise separable convolution and a C3Ghost module are used to replace several C3 modules to reduce the model parameters and improve the detection speed. Then a Squeeze-and-Excitation attention mechanism is integrated into backbone network to improve the accuracy of the algorithm and suppress the environmental interference. Finally, a bidirectional feature pyramid network is used for multi-scale feature fusion to enrich feature information and improve the feature extraction ability of the proposed algorithm. The experimental results demonstrate that compared with the original algorithm, the model weight is reduced by 40 % to only 2.3 M. The mean average precision (mAP@0.5) is increased by 1.7 %. The detection speed reaches 80 FPS, which could accurately detect vehicle targets in real-time.
DOI	10.1016/j.eswa.2022.119108
URL	查看原文
收录类别	sci
语种	英语
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/67021
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	M. L. Bie,Y. Y. Liu,G. N. Li,et al. Real-time vehicle detection algorithm based on a lightweight You-Only-Look-Once (YOLOv5n-L) approach[J]. Expert Systems with Applications,2023,213:9.
APA	M. L. Bie,Y. Y. Liu,G. N. Li,&J. T. Hong and J. Li.(2023).Real-time vehicle detection algorithm based on a lightweight You-Only-Look-Once (YOLOv5n-L) approach.Expert Systems with Applications,213,9.
MLA	M. L. Bie,et al."Real-time vehicle detection algorithm based on a lightweight You-Only-Look-Once (YOLOv5n-L) approach".Expert Systems with Applications 213(2023):9.

条目包含的文件		下载所有文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
Real-time vehicle de（8303KB）	期刊论文	出版稿	开放获取	CC BY-NC-SA	浏览下载