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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Paper Title:	Diabetic retinopathy detection using deep learning
Authors Name:	M.BUVANESWARI , R.SOWNDARYA LAKSHMI , A.SUJITHA
Unique Id:	IJSDR2206060
Published In:	Volume 7 Issue 6, June-2022
Abstract:	Diabetic retinopathy is when damage occurs to the retina due to diabetes, which affects up to 80 percent of all patients who have had diabetes for 10 years or more. The expertise and equipment required are often lacking in areas where diabetic retinopathy detection is most needed. Most of the work in the field of diabetic retinopathy has been based on disease detection or manual extraction of features, but this paper aims at automatic diagnosis of the disease into its different stages using deep learning. This paper presents the design and implementation of GPU accelerated deep convolutional neural networks to automatically diagnose and thereby classify high- resolution retinal images into 5 stages of the disease based on severity. The single model accuracy of the convolutional neural networks presented in this paper is 0.386 on a quadratic weighted kappa metric and ensembling of three such similar models resulted in a score of 0.3996.
Keywords:	deep learning, support vector machine ,PCA
Cite Article:	"Diabetic retinopathy detection using deep learning", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 6, page no.363 - 366, June-2022, Available :http://www.ijsdr.org/papers/IJSDR2206060.pdf
Downloads:	000346990
Publication Details:	Published Paper ID: IJSDR2206060 Registration ID:200651 Published In: Volume 7 Issue 6, June-2022 DOI (Digital Object Identifier): Page No: 363 - 366 Publisher: IJSDR \| www.ijsdr.org ISSN Number: 2455-2631

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