Paper Title
Detecting Diabetic Retinopathy using Deep Learning
Article Identifiers
Authors
Tejas B K
Keywords
convolutional neural networks; deep learning; diabetic retinopathy; image processing.
Abstract
Diabetic Retinopathy (DR) is a vision problem caused by high blood sugar levels damaging the blood vessels in the retina. In order to have effective treatment, it must be detected early. As a result, the purpose of this research is to combine image processing and deep learning approaches to help detect Diabetic Retinopathy early and reduce retinal damage. The methods suggested in this paper include using Convolutional Neural Network (CNN) variants on fundus photography which helps us in detecting Diabetic Retinopathy.
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How To Cite (APA)
Tejas B K (September-2022). Detecting Diabetic Retinopathy using Deep Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 7(9), 1468-1471. https://ijnrd.org/papers/IJNRD2209173.pdf
Issue
Volume 7 Issue 9, September-2022
Pages : 1468-1471
Other Publication Details
Paper Reg. ID: IJNRD_183004
Published Paper Id: IJNRD2209173
Downloads: 000121981
Research Area: Computer Science & TechnologyÂ
Country: Mysuru, Karnataka, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2209173.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2209173
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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