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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 4
1261-1264

Research on semantic segmentation algorithm based on convolutional neural network

Xiong Wei1,2
Tong Lei1
Jin Jingyi1
Wang Chuansheng1
Wang Juan1
Zeng Chunyan1
1. School of Electrical & Electronic Engineering, Hubei University of Technology, Wuhan 430068, China
2. Dept. of Computer Science & Engi-neering, University of South Carolina, Columbia, SC 29201, USA
DOI: 10.19734/j.issn.1001-3695.2019.12.0705

Abstract

In order to solve the problem that the residual network cannot extract image information well and the segmentation effect is poor in semantic segmentation, this paper proposed a joint feature pyramid model to integrate the output features of the residual network, and then further extracted the features in combination with the atrous spatial pyramid pooling module. In the decoding part, this paper applied a simple decoding structure to recover the image size to complete the semantic segmentation. This paper also used attention module as the auxiliary semantic segmentation network to assist the training of the neural network. This method trained the network in the Pascal VOC 2012 data set and the enhanced Pascal VOC 2012 data set respectively, and tested it on the verification set of Pascal VOC 2012. The average ratio of intersection and union(mIoU) is 78.55% and 80.14% respectively, which shows that proposed method has good semantic segmentation performance.

Foundation Support

国家留学基金资助项目(201808420418)
国家自然科学基金资助项目(61571182,61601177)
湖北省自然科学基金资助项目(2019CFB530)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.12.0705
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 4
Section: Technology of Graphic & Image
Pages: 1261-1264
Serial Number: 1001-3695(2021)04-058-1261-04

Publish History

[2021-04-05] Printed Article

Cite This Article

熊炜, 童磊, 金靖熠, 等. 基于卷积神经网络的语义分割算法研究 [J]. 计算机应用研究, 2021, 38 (4): 1261-1264. (Xiong Wei, Tong Lei, Jin Jingyi, et al. Research on semantic segmentation algorithm based on convolutional neural network [J]. Application Research of Computers, 2021, 38 (4): 1261-1264. )

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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