Abstract
In this paper, we present a machine learning approach to detect diabetic retinopathy from retinal images which is one of the most common diseases among diabetic patient. In our experiment, Inception v3 is used as the machine learning approach. Inception is a convolutional neural network classifier by Google. The dataset is collected from Kaggle which contains images of five categories. We used a pretrained model of the classifier which is trained on 1000 classes. We proposed three characterizations of the problem. Our classifier worked better on the first two characterizations than the third one.
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Chowdhury, M.M.H., Meem, N.T.A., Marium-E-Jannat (2020). A Machine Learning Approach to Detect Diabetic Retinopathy Using Convolutional Neural Network. In: Uddin, M., Bansal, J. (eds) Proceedings of International Joint Conference on Computational Intelligence. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-13-7564-4_23
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DOI: https://doi.org/10.1007/978-981-13-7564-4_23
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