Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 6
1889-1893

Target detection algorithm in industrial scene based on SlimYOLOv3

Liu Xinrou
Li Yang
Song Wenjun
School of Electronic & information engineering, Changchun University of Science & Technology, Changchun 130000, China
DOI: 10.19734/j.issn.1001-3695.2020.06.0203

Abstract

The detection speed of detection algorithms based on artificial design features is generally slow, and the detection accuracy needs to be improved, which can no longer meet the needs of today's industrial production. The detection technology based on deep learning cannot be deployed on resource-constrained devices because it requires a lot of computing and storage space. In response to these problems, this paper cited a channel pruning method to realize the lightweight of the YOLOv3 detection network, and obtained the pruning model SlimYOLOv3, and proposed to use SlimYOLOv3 for real-time detection tasks in industrial scenarios. The method enhanced the channel-level sparsity of the convolutional layer by applying L1 regularization to the channel scaling factor, and pruned the feature channels with less information, and obtained a lightweight network model. Compared with the original model, SlimYOLOv3 gives a 60% reduction in model size and a 50% reduction in computing ope-rations, the detection speed is 1.7 times of the original model. It is more suitable for real-time detection of complex targets in intelligent industrial scenes.

Foundation Support

中国吉林省科学技术计划发展项目(20180201042GX)
吉林省预算内基本建设资金资助项目(创新能力建设—高技术产业部分)(2019C054-b)
中国吉林省科学技术计划发展项目(20200401090GX)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.06.0203
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 6
Section: Technology of Graphic & Image
Pages: 1889-1893
Serial Number: 1001-3695(2021)06-055-1889-05

Publish History

[2021-06-05] Printed Article

Cite This Article

刘馨柔, 李洋, 宋文军. 基于SlimYOLOv3的工业场景目标检测算法 [J]. 计算机应用研究, 2021, 38 (6): 1889-1893. (Liu Xinrou, Li Yang, Song Wenjun. Target detection algorithm in industrial scene based on SlimYOLOv3 [J]. Application Research of Computers, 2021, 38 (6): 1889-1893. )

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  • 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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