A Deep Learning Neural Network for Detecting the Diabetic Retinopathy
R. Raja Kumar1, G. Kishor Kumar2, M.K. Koushik3, M. Chennakesavulu4

1Dr R. Raja Kumar, Department of Computer Science Engineering, RGMCET, Nandyal, India.
2Dr G. Kishor Kumar, Department of Information Technology, RGMCET, Nandyal, India.
3M.K. Koushik, Department of Information Technology, RGMCET, Nandyal, India
4M Chennakesavulu, Department of Information Technology, RGMCET, Nandyal, India
Manuscript received on 01 August 2019 | Revised Manuscript received on 09 August 2019 | Manuscript published on 30 August 2019 | PP: 3522-3525 | Volume-8 Issue-10, August 2019 | Retrieval Number: J97460881019/19©BEIESP | DOI: 10.35940/ijitee.J9746.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Diabetic Retinopathy (DR) is the leading cause of disease to blindness of people globally. The retinal screening examinations of diabetic patients is needed to prevent the disease. There are many untreated and undiagnosed cases present in especially in India. DR requires smart technique to detect it. In this paper, we proposed a deep learning based architecture for detecting the DR. The experiments are done on the DR Dataset available in UCI machine Learning Repository. The results obtained from the experiments are satisfactory.
Keywords: Diabetic Retinopathy, Deep Learning, Neural Network, UCI

Scope of the Article: Deep Learning