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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 5
1590-1594

Light-weight object detection network based on group convolution and feature maps cascade

Yang Xianzhi1
Huang Guofang2
Zhou Ningning1
1. School of Computer Science, Nanjing University of Posts & Telecommunications, Nanjing 210023, China
2. NARI Technology Co. Ltd. , Nanjing 211106, China
DOI: 10.19734/j.issn.1001-3695.2020.05.0154

Abstract

To solve the shortcomings such as a large number of parameters, a large number of FlOPs and poor detection accuracy in the Pelee light-weight object detection network, this paper proposed an improved version named GCPelee based on grouped convolution and feature maps cascade. Firstly, it reduced the amount of model parameters and FLOPs by replacing normal convolution in the detection module with group convolution. Secondly, it applied feature maps cascade on the detection module to transmitted the information contained in the feature maps with a large receptive field to the feature maps with a small one, which would enlarge the receptive field of the latter. The experimental results show that the GCPelee model gets higher detection accuracy with less parameters and less FLOP.

Foundation Support

智能电网保护和运行控制国家重点实验室开放课题(201610,20169)
国家自然科学基金资助项目(61170322,61373065,61302157)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.05.0154
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 5
Section: Technology of Graphic & Image
Pages: 1590-1594
Serial Number: 1001-3695(2021)05-059-1590-05

Publish History

[2021-05-05] Printed Article

Cite This Article

杨贤志, 黄国方, 周宁宁. 基于分组卷积和特征图级联的轻量级目标检测 [J]. 计算机应用研究, 2021, 38 (5): 1590-1594. (Yang Xianzhi, Huang Guofang, Zhou Ningning. Light-weight object detection network based on group convolution and feature maps cascade [J]. Application Research of Computers, 2021, 38 (5): 1590-1594. )

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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