To Develop An Optimal Classifier For The diagnosis Of Diabetic Retinal Images Using Computational Intelligence Techniques.

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ISSN: 2349-6002 ESTD Year: 2014

UGC approved journal no 47859

To Develop An Optimal Classifier For The diagnosis Of Diabetic Retinal Images Using Computational Intelligence Techniques.
Author(s):
Pradnya Bhagwant Sawade, Dr. V L Agrawal
Keywords:
Neural network, Microsoft excel, MatLab, normal and diabetic retina scan images.
Abstract
In this paper classification normal and diabetic retina scan images , which uses the FFT transform over the retina images as feature detector and a constructive one hidden layer Generalized feed forward neural network as classification normal and diabetic retina scan images classifier technique is applied to a database consisting of images of 145 having normal and dibetic retina scan images. It is demonstrated that the best recognition rates are 99.70%. Finally, optimal algorithm has been developed on the basis of the best classifier performance. The algorithm will provide an effective alternative method of Classification of Diabetic Retinopathy using Neural Network Approach.
Article Details
Unique Paper ID: 154485 Publication Volume & Issue: Volume 8, Issue 11 Page(s): 268 - 273
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