An efficient early detection of diabetic retinopathy using dwarf mongoose optimization based deep belief network-Reference-Cited by-同舟云学术

An efficient early detection of diabetic retinopathy using dwarf mongoose optimization based deep belief network

Published:2022-10-07 Issue:28 Volume:34 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency and Computation

Author:

Abirami A.¹^ORCID,Kavitha R.²^ORCID

Affiliation:

1. Research Scholar, Department of Computer Science and Engineering SRM Institute of Science and Technology, SRM University Chennai India

2. Department of Information Technology SRM Institute of Science and Technology, SRM University Chennai India

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.7364

Reference33 articles.

1. An automatic detection system of diabetic retinopathy using a hybrid inductive machine learning algorithm;Mahmoud MH;Pers Ubiquitous Comput,2021

2. Diabetic Retinopathy Detection Using VGG-NIN a Deep Learning Architecture

3. Threshold segmentation based multi‐layer analysis for detecting diabetic retinopathy using convolution neural network;Shanthini A;J Ambient Intell Humaniz Comput Secur,2021

4. TymchenkoB MarchenkoP SpodaretsD.Deep learning approach to diabetic retinopathy detection. arXiv preprint arXiv:2003.02261; 2020.

5. Hierarchical severity grade classification of non-proliferative diabetic retinopathy

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