Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 8
2545-2549

Vehicle detection method based on MobileVit lightweight network

Xiong Liyan1a
Tu Suocheng1a
Huang Xiaohui1a
Yu Junying1a
Xie Yunchi2
Huang Weichun1b
1. a. School of Information Engineering, b. Network Information Center, East China Jiaotong University, Nanchang 330013, China
2. Dept. of Transport, Traffic Monitoring & Command Center of Jiangxi Provincial, Nanchang 330036, China
DOI: 10.19734/j.issn.1001-3695.2021.12.0684

Abstract

In view of the large amount of vehicle detection model parameters and missing detection of small targets and occluded targets, this paper presented a vehicle detection algorithm based on lightweight MobileVit. Firstly, in the data preprocessing stage, the method used GridMask image enhancement to improve the performance of occluded target detection. Secondly, the method used MobileVit network as the backbone feature extraction network of the model to fully extract the feature information and make the model lightweight. Finally, in the prediction layer network, the method used multiscale vehicle detection and recognition based on PANet network to improve the detection performance of the model for small targets. The experimental results show that the average detection accuracy of this algorithm is 98.24%, the detection speed is 0.058 s per picture, and the model size is 136 MB, compared with the comparison algorithm, the comprehensive performance is better.

Foundation Support

江西省交通厅科技资助项目(2021X0011,2022X0040)
国家自然科学基金资助项目(62067002,61967006,62062033)
江西省自然科学基金资助项目(20212BAB202008)
江西省教育厅资助项目(GJJ190317)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.12.0684
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 8
Section: Technology of Graphic & Image
Pages: 2545-2549
Serial Number: 1001-3695(2022)08-053-2545-05

Publish History

[2022-03-09] Accepted Paper
[2022-08-05] Printed Article

Cite This Article

熊李艳, 涂所成, 黄晓辉, 等. 基于MobileVit轻量化网络的车辆检测方法 [J]. 计算机应用研究, 2022, 39 (8): 2545-2549. (Xiong Liyan, Tu Suocheng, Huang Xiaohui, et al. Vehicle detection method based on MobileVit lightweight network [J]. Application Research of Computers, 2022, 39 (8): 2545-2549. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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