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Diabetic Retinopathy Stage Classification

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Document pages: 11 pages

Abstract: Diabetic Retinopathy is the disease of the retina caused by long-standing diabetes leading to damage of the retina and can even lead to blindness. Diabetic Retinopathy stage classification deals with different stages of diabetes and has been considered as the most important step in the analysis of the disease. Diagnosis of the disease manually requires skilled individuals to identify distinct features, which is a difficult and time-consuming task. In this paper, a deep learning-based CNN model for diagnosing is presented. Digital color fundus images are used. In this work, we have implemented an InceptionV3 model with an attention mechanism. The motive behind using attention mechanism was that the model should pay more attention to the relevant portion of the image. This work will enable a user to test their eyes and can be easily identified in which stage of diabetes they are suffering. All the images were divided into five groups. In the proposed work, the CNN model (InceptionV3) was trained for producing a model for predicting on validation samples. Categorical accuracy of 60.82 is achieved with a Top 2 accuracy of 82.16.

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