| Autor: |
Pak, Alexandr1 (AUTHOR) alexpak1983@gmail.com, Ziyaden, Atabay1 (AUTHOR) iamdenay@gmail.com, Tukeshev, Kuanysh1,2 (AUTHOR) zau-24@mail.ru, Jaxylykova, Assel1 (AUTHOR) aselya17.89@mail.ru, Abdullina, Dana1,2 (AUTHOR) hirurg01@mail.ru, Pham, Duc3 (AUTHOR) |
| Předmět: |
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| Zdroj: |
Cogent Engineering. Jan2020, Vol. 7 Issue 1, p1-21. 21p. |
| Abstrakt: |
Diabetic retinopathy is a common complication of diabetes, that affects blood vessels in the light-sensitive tissue called the retina. It is the most common cause of vision loss among people with diabetes and the leading cause of vision impairment and blindness among working-age adults. Recent progress in the use of automated systems for diabetic retinopathy diagnostics has offered new challenges for the industry, namely the search for a less resource-intensive architecture, e.g., for the development of low-cost embedded software. This paper proposes a comparison between two widely used conventional architectures (DenseNet, ResNet) with the new optimized one (EfficientNet). The proposed methods classify the retinal image as one of 5 class cases based on the dataset obtained from the 4th Asia Pacific Tele-Ophthalmology Society (APTOS) Symposium. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Library, Information Science & Technology Abstracts |
| Externí odkaz: |
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