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@article{156639,
        author = {P.REVATHI and Dr. S. MOHIDEEN ABDUL KADHAR},
        title = {Detection of Diabetic Retinopathy Using Convolutional Neural Network},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {4},
        pages = {273-277},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=156639},
        abstract = {The objective of this paper is to develop a model for diabetic retinopathy, a prime cause for blindness that appears due to diabetes. A deep learning model based on fully convolutional neural network is developed to classify the disease from images of the patient. The combination of multi-structure morphological process and Segmentation technique is used effectively for retinal vessel detection to identify diabetic retinopathy using a neural network. The method is accomplished through various steps: Data Collection, Pre-processing, Augmentation and modelling. Our proposed model achieved 90% of accuracy. The Regression model was also employed, manifested up an accuracy of 78%. The main aim of this work is to develop a robust system for detecting DR automatically.},
        keywords = {Diabetic Retinopathy, Convolutional Neural Network.},
        month = {},
        }