Diabetic Retinopathy Diagnosis Using Retinal Fundus Images through MobileNetV3
- Title
- Diabetic Retinopathy Diagnosis Using Retinal Fundus Images through MobileNetV3
- Creator
- Sejal A.Y.; Thiruthuvanathan M.M.
- Description
- Diabetic Retinopathy (DR) is a major disease throughoutthe world. Diagnosis of diabetes at an early stage is so critical and could help save several lifestyles. One out of two individuals experiencing diabetes has been determined to have some phase of DR. Recognition of DR symptoms in time can turn away the vision weakness inmost the cases, nonetheless, such disclosure is troublesome with present devices and strategies. Existingmethods for determining whether a person is suffering from diabetes or maybe the chances of acquiring diabetesrely heavily on examiners. Most of the time, it can be treated if caught during the early stages. There is a need for creating models that are efficient and robust to detect DR holistically. In recent times the advent of Deep learning models has been used extensively in various Bio medical applications. In this work, we utilize a Hyper parameter tuned MobileNet-V3 model based on a multi-stage Convolutional Neural Network (CNN) to efficiently classify images from the IRDID dataset. A Multiclass classification model involving images collated from various sources were trained, validated and tested for classification accuracy. The network was evaluated based on parameters and the network was able to achieve an accuracy of 88.6% 2023 IEEE.
- Source
- Proceedings of IEEE InC4 2023 - 2023 IEEE International Conference on Contemporary Computing and Communications
- Date
- 2023-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Convolutional Neural Network; Diabetic Retinopathy (DR); MobileNet-V3; Proliferative; Retinal Fundus Image
- Coverage
- Sejal A.Y., CHRIST(Deemed to Be University), Computer Science and Engineering, Bengaluru, India; Thiruthuvanathan M.M., CHRIST(Deemed to Be University), Computer Science and Engineering, Bengaluru, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835033577-4
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Sejal A.Y.; Thiruthuvanathan M.M., “Diabetic Retinopathy Diagnosis Using Retinal Fundus Images through MobileNetV3,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 26, 2025, https://archives.christuniversity.in/items/show/19837.