A Study on Diabetic Retinopathy Detection, Segmentation and Classification using Deep and Machine Learning Techniques
Author:
Affiliation:
1. VIT-AP University,School of CSE,Amaravathi,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9776594/9776641/09776690.pdf?arnumber=9776690
Reference24 articles.
1. Detection of microaneurysms using ant colony algorithm in the early diagnosis of diabetic retinopathy
2. Diabetic Retinopathy Segmentation and Classification using Deep Learning Approach;nallasivan;Annals of the Romanian Society for Cell Biology,2021
3. Presentation of a Segmentation Method for a Diabetic Retinopathy Patient’s Fundus Region Detection Using a Convolutional Neural Network
4. Segmentation of Microaneurysms for Early Detection of Diabetic Retinopathy using MResUNet;oomariah;International Journal of Intelligent Envineerinv and Systems,2021
5. Deep Bayesian baseline for segmenting diabetic retinopathy lesions: Advances and challenges
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3. Automated Diagnosis of Eye Problems Using Deep Learning Techniques on Retinal Fundus Images;Meta-Learning Frameworks for Imaging Applications;2023-09-28
4. Transfer Learning for Diabetic Retinopathy Detection: A Study of Dataset Combination and Model Performance;Applied Sciences;2023-05-05
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