Abstract
A complication of diabetes is a disease called diabetic retinopathy (DR). Diabetic retinopathy is one of the most serious eye diseases and can cause the loss of vision in people suffering from diabetes. It is especially dangerous because it frequently goes unnoticed and, if not caught in time, can result in severe damage or even the loss of eyesight. There have been many advancements in computer science and image processing that are effective in detecting DR by classifying retinal images from patients. Such a method typically relies on huge and carefully described dataframes. Hence, we propose a comparative analysis of the few of the different approaches for classifying and detecting DR through CNN.
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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Prasad, V.K., Nimavat, V., Trivedi, K., Bhavsar, M. (2023). Utilizing Deep Learning Methodology to Classify Diabetic Retinopathy. In: Ranganathan, G., Papakostas, G.A., Rocha, Á. (eds) Inventive Communication and Computational Technologies. ICICCT 2023. Lecture Notes in Networks and Systems, vol 757. Springer, Singapore. https://doi.org/10.1007/978-981-99-5166-6_46
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DOI: https://doi.org/10.1007/978-981-99-5166-6_46
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