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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 7
2183-2189,2195

Lightweight fundus disease multi-classification network with multi-scale bilinear attention

Li Chaolin
Zhang Rongfen
Liu Yuhong
College of Big Data & Information Engineering, Guizhou University, Guiyang 550025, China
DOI: 10.19734/j.issn.1001-3695.2021.12.0664

Abstract

Most of the eye disease classification methods are to classify a single category of diseases at different levels, and the network model has problems such as large parameters and complex calculations. To solve these problems, this paper proposed a lightweight fundus disease multi-classification network called MELCNet. The network used PPLCNet as the backbone, which was composed of input layer for feature extraction, parallel multi-scale structure, bilinear SE attention module, depth separable convolution and the h-swish activation function which calculated with smaller parameters, in order to pay attention to the key disease information of different scales and different diseases. Experimental results show that the proposed multi-scale attention lightweight network model has less parameters and computational complexity, and excellent classification results have been obtained in the multi-classification of the four selected fundus diseases and normal fundus images. The classification accuracy in the internal combined test set is 1.11% higher than that in ResNet-50, and the performance on the public datasets is improved by 2.5% relative to the multi-classification literature of similar type network by Xie et al, and compared with other lightweight classification networks, it has higher accuracy and strong robustness in the field of multi-classification of fundus diseases.

Foundation Support

贵州省科学技术基金资助项目(黔科合基础[2019]1099)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.12.0664
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 7
Section: Technology of Graphic & Image
Pages: 2183-2189,2195
Serial Number: 1001-3695(2022)07-043-2183-07

Publish History

[2022-02-16] Accepted Paper
[2022-07-05] Printed Article

Cite This Article

李朝林, 张荣芬, 刘宇红. 融入多尺度双线性注意力的轻量化眼底疾病多分类网络 [J]. 计算机应用研究, 2022, 39 (7): 2183-2189,2195. (Li Chaolin, Zhang Rongfen, Liu Yuhong. Lightweight fundus disease multi-classification network with multi-scale bilinear attention [J]. Application Research of Computers, 2022, 39 (7): 2183-2189,2195. )

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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