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@article{154485,
        author = {Pradnya Bhagwant Sawade and Dr. V L Agrawal},
        title = {To Develop An Optimal Classifier For The diagnosis Of Diabetic Retinal Images Using Computational Intelligence Techniques.},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {11},
        pages = {268-273},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=154485},
        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.},
        keywords = {Neural network, Microsoft excel, MatLab, normal and diabetic retina scan images.},
        month = {},
        }