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Improved Model of Eye Disease Recognition Based on VGG Model

Ye Mu1,2,3,4, Yuheng Sun1, Tianli Hu1,2,3,4, He Gong1,2,3,4, Shijun Li1,2,3,4,*, Thobela Louis Tyasi5

1 College of Information Technology, Jilin Agricultural University, Changchun, 130118, China
2 Jilin Province Agricultural Internet of Things Technology Collaborative Innovation Center, Changchun, 130118, China
3 Jilin Province Intelligent Environmental Engineering Research Center, Changchun, 130118, China
4 Jilin Province colleges and universities The 13th Five-Year Engineering Research Center, Changchun, 130118, China
5 Department of Agricultural Economics and Animal Production, University of Limpopo, 0727, Polokwane, South Africa

* Corresponding Author: Shijun Li. Email: email

Intelligent Automation & Soft Computing 2021, 28(3), 729-737.


The rapid development of computer vision technology and digital images has increased the potential for using image recognition for eye disease diagnosis. Many early screening and diagnosis methods for ocular diseases based on retinal images of the fundus have been proposed recently, but their accuracy is low. Therefore, it is important to develop and evaluate an improved VGG model for the recognition and classification of retinal fundus images. In response to these challenges, to solve the problem of accuracy and reliability of clinical algorithms in medical imaging this paper proposes an improved model for early recognition of ophthalmopathy in retinal fundus images based on the VGG training network of densely connected layers. To determine whether the accuracy and reliability of the proposed model were greater than those of previous models, our model was compared to ResNet, AlexNet, and VGG by testing them on a retinal fundus image dataset of eye diseases. The proposed model can ultimately help accelerate the diagnosis and referral of these early eye diseases, thereby facilitating early treatment and improved clinical outcomes.


Cite This Article

Y. Mu, Y. Sun, T. Hu, H. Gong, S. Li et al., "Improved model of eye disease recognition based on vgg model," Intelligent Automation & Soft Computing, vol. 28, no.3, pp. 729–737, 2021.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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