Technology of Graphic & Image
|
919-923

Object recognition method based on lightweight depth network

Li Yahui
Liu Jun
Laboratory of Fundamental Science on Communication Information Transmission & Fusion Technology, Hangzhou Dianzi University, Hangzhou 310018, China

Abstract

Aiming at the task of object recognition under resource constrained condition, this paper proposed a method of object recognition based on light weight depth network. By optimizing the design method of the network structure such as convolution operation, model parameter compression and enhancement of feature expression depth, this paper designed and implemented the lightweight network model structure named Se-DResNet for embedded platform. So that the depth network model could reduce the parameters of the model and the resources needed for operation under the condition of guaranteeing the precision. The experimental results show that the lightweight depth model has better performance than that of the basic model ResNet proposed by ILSVRC-15 champion, and it can achieve the model accuracy of 93.5% under the condition that the model with 10.2% fewer parameters on ImageNet-67 data set.

Foundation Support

国家自然科学基金重点资助项目
海军装备预研创新项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.07.0663
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 3
Section: Technology of Graphic & Image
Pages: 919-923
Serial Number: 1001-3695(2020)03-062-0919-05

Publish History

[2020-03-05] Printed Article

Cite This Article

李亚辉, 刘俊. 基于轻量级深度网络的目标识别方法 [J]. 计算机应用研究, 2020, 37 (3): 919-923. (Li Yahui, Liu Jun. Object recognition method based on lightweight depth network [J]. Application Research of Computers, 2020, 37 (3): 919-923. )

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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