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DIABETIC RETINOPATHY USING DEEP LEARNING
Diabetic retinopathy is becoming a more prevalent disease in diabetic patients nowadays. Diabetic Retinopathy is one of the leading causes of blindness and eye disease in the working age population of the developed world. This project is an attempt towards finding an automated way to detect this disease in its early phase. In this project we are using supervised learning methods to classify a given set of images into 2 classes to verify that the patient has a scope for Diabetic Retinopathy. For this task we are employing various image processing techniques and filters to enhance many important features and then using neural for classification.
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