IJRTI
International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)

Call For Paper

For Authors

Forms / Download

Published Issue Details

Editorial Board

Other IMP Links

Facts & Figure

Impact Factor : 8.14

Issue per Year : 12

Volume Published : 10

Issue Published : 113

Article Submitted : 18245

Article Published : 7789

Total Authors : 20583

Total Reviewer : 750

Total Countries : 142

Indexing Partner

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Published Paper Details
Paper Title: DIABETIC RETINOPATHY DETECTION USING CONVOLUTIONAL NEURAL NETWORKS
Authors Name: SHERIN THOMAS , NANDANA V , NAVANEETH BABU , NEERAJ NANDAN , RESHMI S
Download E-Certificate: Download
Author Reg. ID:
IJRTI_185567
Published Paper Id: IJRTI2303074
Published In: Volume 8 Issue 3, March-2023
DOI:
Abstract: Diabetes is one of the most common health issues that we come across in our lives. Most of the people are unaware of the consequences of not taking care of the same. Diabetes leads to a lot of health dilemmas, one of which being Diabetic Retinopathy. Diabetes leads to rise in blood sugar level which in turn becomes the source for the development of Diabetic Retinopathy and having too much sugar can damage the retina over time along with damage of optical nerve in the long run. Diabetic Retinopathy can even lead to blindness if not treated properly in the early stages. Convolutional Neural Networks can be used efficiently for the detection of Diabetic Retinopathy. The fundus images of retina can be tested using a well-trained network and the disease as well as its current stage can be determined. Some of the existing networks namely- VGG16, Resnet50 and Inception V3 have been trained with the datasets from kaggle. The most efficient network being Inception V3 is selected and has been trained and tested with the external dataset collected from Government Medical College, Thrissur. Hyperparameter tuning has also been studied with the parameters learning rate, epoch, decay and momentum, giving a wider picture of how effective CNN can be in diagnosing Diabetic Retinopathy.
Keywords: Classification, CNN, Diabetic retinopathy, Fundus images
Cite Article: "DIABETIC RETINOPATHY DETECTION USING CONVOLUTIONAL NEURAL NETWORKS", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 3, page no.432 - 436, March-2023, Available :http://www.ijrti.org/papers/IJRTI2303074.pdf
Downloads: 000205132
ISSN: 2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID: IJRTI2303074
Registration ID:185567
Published In: Volume 8 Issue 3, March-2023
DOI (Digital Object Identifier):
Page No: 432 - 436
Country: Kasargod, Kerala, India
Research Area: Bio Medical Engineering 
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2303074
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2303074
Share Article:

Click Here to Download This Article

Article Preview
Click Here to Download This Article

Major Indexing from www.ijrti.org
Google Scholar ResearcherID Thomson Reuters Mendeley : reference manager Academia.edu
arXiv.org : cornell university library Research Gate CiteSeerX DOAJ : Directory of Open Access Journals
DRJI Index Copernicus International Scribd DocStoc

ISSN Details

ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED, Journal Starting Year (ESTD) : 2016

DOI (A digital object identifier)


Providing A digital object identifier by DOI.ONE
How to Get DOI?

Conference

Open Access License Policy

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Creative Commons License This material is Open Knowledge This material is Open Data This material is Open Content

Important Details

Join RMS/Earn 300

IJRTI

WhatsApp
Click Here

Indexing Partner