A broad study of machine learning and deep learning techniques for diabetic retinopathy based on feature extraction, detection and classification-Reference-Cited by-同舟云学术

A broad study of machine learning and deep learning techniques for diabetic retinopathy based on feature extraction, detection and classification

Published:2023-12 Issue: Volume:30 Page:100951
ISSN:2665-9174
Container-title:Measurement: Sensors
language:en
Short-container-title:Measurement: Sensors

Author:

Sangeetha Krishnan,Valarmathi K.,Kalaichelvi T.,Subburaj S.

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Mechanics of Materials,Electronic, Optical and Magnetic Materials

Reference50 articles.

1. Detection of diabetic retinopathy using extracted 3D features from OCT images;MDPI,2022

2. Diabetic Retinopathy Detection Using Genetic Algorithm Based CNN Features and Error Correction Output Code SVM Framework Classification Model, Wireless Communications and Mobile Computing,2022

3. Diabetic retinopathy improved detection using machine learning;MDPI,2021

4. Proposed international clinical diabetic retinopathy and diabetic macular edema disease severity scales;Wilkinson;Am. Acad.Ophthalmol.,2003

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