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
Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 729-737, 2021, DOI:10.32604/iasc.2021.016569
Abstract 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… More >
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