Abstract
Modular feedforward network method is introduced to detect diabetic retinopathy in retinal images. In this paper, the authors present classification method; the Modular Feedforward Neural Network (MNN) to classify retinal images as normal and abnormal. Publically available database such as DIARETDB0 including high-quality normal and abnormal retinal images is taken for detection of diabetic retinopathy. Modular Feedforward Neural Network is designed based on the extracted features of retinal images and the train N times method. The classification accuracy by MNN classifier was 100% for normal retinal images and 86.67% for abnormal retinal images. In this paper, the authors have explored such a method using MNN classifier which can detect diabetic retinopathy by classifying retinal images as normal and abnormal.
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Sharma, M., Sharma, P., Saini, A., Sharma, K. (2018). Modular Neural Network for Detection of Diabetic Retinopathy in Retinal Images. In: Somani, A., Srivastava, S., Mundra, A., Rawat, S. (eds) Proceedings of First International Conference on Smart System, Innovations and Computing. Smart Innovation, Systems and Technologies, vol 79. Springer, Singapore. https://doi.org/10.1007/978-981-10-5828-8_35
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DOI: https://doi.org/10.1007/978-981-10-5828-8_35
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