Python
Deep Learning
2023
ID: 1CP0684
Classification of Diabetic Retinopathy and Retinal Images Using VGG16 and SVM
Keywords:
Diabetic
Retinopathy,
VGG16,
Support
Vector
Machine,
Retinal
Fundus
Images,
Deep
Learning,
Image
Classification,
Feature
Extraction,
Medical
Imaging
Project Synopsis & Overview
This project classifies diabetic retinopathy stages from retinal fundus images using a hybrid deep learning approach. Images are collected, preprocessed, and split into training and testing sets. VGG16 extracts features, and a Support Vector Machine classifies them into No DR, Mild, Moderate, Severe, and Proliferative stages. Comparing both models supports faster, accurate, automated screening and early detection of vision-threatening disease.
Complete Technical Specifications
| Project ID | 1CP0684 (DB ID: 684) |
| Project Title | Classification of Diabetic Retinopathy and Retinal Images Using VGG16 and SVM |
| Domain Division | Python |
| Sub-Domain / Tech | Deep Learning |
| IEEE Year | 2023 |
| Package Price | ₹6500 |
| Created Date | Nov 11, 2026 |
Project Price
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₹8000
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