Neural Network Based Approach for Detection and Classification of Diabetic Retinopathy


  • Vinod S. Wadne Department of Computer Engineering, JSPM’s ICOER, Wagholi, Pune, India
  • Ashish P. Gaigol Department of Computer Engineering, JSPM’s ICOER, Wagholi, Pune, India
  • Shubham R. Bhandari Department of Computer Engineering, JSPM’s ICOER, Wagholi, Pune, India
  • Rekha S. Kotwal Department of Information Technology, JSPM’s BSIOTR, Wagholi, Pune,India
  • Suvarna A. Wakure Department of Electronics and Telecommunication Trinity Academy of Engineering, Pune, India
  • Rupesh G. Mahajan Department of Computer Engineering, Dr. D. Y. Patil Institute of Technology, Pune


CNN, Retinal Image, Matrix, Diabetic, Retonopathy (DR)


Prolonged diabetes DR can cause eye abnormalities. As the pain progresses, it can cause paralysis and blindness. Evaluation of DR using the shadow fundus is a difficult and time – consuming task because the physician must determine the visual perception of light. We propose to use CNNs to analyse DR from computer images. In our research, we use a different technique by dividing the entire image into parts and performing additional operations only on the region of interest. The planning process clearly outlines disaster recovery and helps connect clients with expert professionals. This allows customers to share their questions and get qualified members on medical topics.



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How to Cite

Wadne, V. S. ., Gaigol, A. P. ., Bhandari, S. R. ., Kotwal, R. S. ., Wakure, S. A. ., & Mahajan, R. G. . (2023). Neural Network Based Approach for Detection and Classification of Diabetic Retinopathy. International Journal of Intelligent Systems and Applications in Engineering, 12(4s), 180–186. Retrieved from



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