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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 5
1578-1581

Research on expression recognition based on improved deep residual network

He Jun
Liu Yue
Li Changhong
Shen Jinming
Li Shuai
Wang Jingwei
School of Information Engineering, Nanchang University, Nanchang 330031, China
DOI: 10.19734/j.issn.1001-3695.2018.10.0846

Abstract

This paper proposed an improved residual network(ResNet) expression recognition algorithm. The algorithm used small convolution kernels and a deep network structure to solve the problem of accuracy reduction with the increase of depth by the residual module. The experiment overcame the shortcoming of insufficient data through transfer learning, which could effectively prevent overfitting. The network architecture used a linear SVM for classification. The experiment used the ImageNet database to pre-train network parameters to have an excellent ability to extract feature. According to transfer learning, the algorithm used the FER-2013 database and the expanded CK+database to fine-tune and train network parameters, and overcame the problem that shallow networks rely on manual features and deep networks were difficult to train. The results show the recognition rates is 91.333% and 95.775% on the CK+database and the GENKI-4K database, respectively. The classification accuracy of SVM in CK+database is about 1% higher than that of softmax.

Foundation Support

国家自然科学基金资助项目(61463034)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.10.0846
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 5
Section: Technology of Graphic & Image
Pages: 1578-1581
Serial Number: 1001-3695(2020)05-062-1578-04

Publish History

[2020-05-05] Printed Article

Cite This Article

何俊, 刘跃, 李倡洪, 等. 基于改进的深度残差网络的表情识别研究 [J]. 计算机应用研究, 2020, 37 (5): 1578-1581. (He Jun, Liu Yue, Li Changhong, et al. Research on expression recognition based on improved deep residual network [J]. Application Research of Computers, 2020, 37 (5): 1578-1581. )

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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