Hybrid CNN-SVD Based Prominent Feature Extraction and Selection for Grading Diabetic Retinopathy Using Extreme Learning Machine Algorithm

Hybrid CNN-SVD Based Prominent Feature Extraction and Selection for Grading Diabetic Retinopathy Using Extreme Learning Machine Algorithm

This paper exploits the extreme learning machine (ELM) approach to address diabetic retinopathy (DR), a medical condition in which impairment occurs to the retina caused by diabetes. DR, a leading cause of blindness worldwide, is a sort of swelling leakage due to excessive blood sugar in the retina...

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Auteurs principaux: Md. Nahiduzzaman, Md. Robiul Islam, S. M. Riazul Islam, Md. Omaer Faruq Goni, Md. Shamim Anower, Kyung-Sup Kwak
Format: article
Langue:EN
Publié: IEEE 2021
Sujets:
Ben Graham’s pre-processing
contrast limited adaptive histogram equalization (CLAHE)
convolutional neural network-singular value decomposition (CNN-SVD)
diabetic retinopathy (DR)
extreme learning machine (ELM)
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
Accès en ligne:https://doaj.org/article/bd326b8c15104142953d12d645ba0f7f
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https://doaj.org/article/bd326b8c15104142953d12d645ba0f7f

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