|
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
Imp Links for Author
Imp Links for Reviewer
Research Area
Subscribe IJSDR
Visitor Counter
Copyright Infringement Claims
Indexing Partner
|
Published Paper Details
|
|
| Paper Title: | Efficient Classification of Diabetic Retinopathy Stages using VGG-NIN Deep Learning Architecture |
| Authors Name: | Neelam Shashikant Nikale , Dr Swati Bhavsar |
| Unique Id: | IJSDR2404182 |
| Published In: | Volume 9 Issue 4, April-2024 |
| Abstract: | Diabetic retinopathy (DR) is a serious condition that damages retinal blood vessels, potentially leading to blindness. Traditional diagnosis involves manual analysis of colored fundus images by clinicians, which is error-prone and time-consuming. To mitigate these challenges, computer vision techniques have been utilized for automating DR detection. However, existing methods often struggle with computational complexity and inadequate feature extraction for precise DR stage classification. This paper introduces a novel approach for classifying DR stages with minimal learnable parameters to enhance training efficiency and model convergence. The VGG16 architecture, augmented with a spatial pyramid pooling layer (SPP) and network-in-network (NiN) structures, constitutes the VGG-NiN model, capable of effectively processing DR images across different scales due to the adaptability of the SPP layer. Moreover, the incorporation of NiN enhances the model's ability to capture nonlinear features, thereby improving classification accuracy. Experimental findings validate the efficacy of the proposed model, demonstrating superior performance in terms of accuracy and computational efficiency compared to existing techniques. |
| Keywords: | CNN, colored fundus images, diabetic retinopathy, deep learning |
| Cite Article: | "Efficient Classification of Diabetic Retinopathy Stages using VGG-NIN Deep Learning Architecture", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.9, Issue 4, page no.1249 - 1254, April-2024, Available :http://www.ijsdr.org/papers/IJSDR2404182.pdf |
| Downloads: | 000338171 |
| Publication Details: | Published Paper ID: IJSDR2404182 Registration ID:210932 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: 1249 - 1254 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijsdr.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 |
Track Paper
Important Links
Conference Proposal
ISSN
 |
 |
DOI (A digital object identifier)
  Providing A digital object identifier by DOI How to GET DOI and Hard Copy Related |
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
 |
 |
 |
Social Media
Indexing Partner |
|||
| Copyright © 2024 - All Rights Reserved - IJSDR | |||
Facebook Twitter Instagram LinkedIn