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

Pradnya Bhagwant Sawade; Dr. V L Agrawal

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

Authors: Pradnya Bhagwant Sawade, Dr. V L Agrawal

Unique Paper ID: 154485
Volume: 8
Issue: 11
PageNo: 268-273

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.

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ISSN: 2349-6002
Volume: 8
Issue: 11
PageNo: 268-273

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

Available:https://ijirt.org/Article?manuscript=154485

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8.01 (Year 2024)

UGC Approved
Journal no 47859

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