• Nayanbhai Soni
• Dr. Mukta Agarwal

The main reason for blindness in India and other nations is diabetic retinopathy. Millions of individuals worldwide are impacted by DR, which results in blindness and vision loss. Early detection of diabetes mellitus is crucial for avoiding the potential loss of vision that can occur if the condition is not treated for an extended length of time. As diabetic retinopathy can result in blindness in people with uncontrolled diabetes, it is becoming more and more crucial to identify it early using automated technologies rather than human screening techniques like fluorescein angiography, optical coherence tomography, etc. On machine learning and deep learning-based DR detection systems, numerous papers have been published.We examine the fundamentals of cutting-edge AI technologies utilized in DR analysis and early detection in this research. Reviewing DR detection methods from several perspectives, including datasets, picture preprocessing, methods, machine learning and deep learning-based approaches, and performance measurements, is the goal of this paper. It includes both the review's findings and the authors' observations.In the area of DR detection, many public datasets were accessible. Based on shape, texture, and statistical data, the Artificial Neural Network outperformed previous machine learning techniques for DR detection. This study's goal is to review the performance of the Convolutional Neural Network (CNN).

Convolutional Neural Network (CNN), Retinal Fundus Images, Ophthalmology, Diabetic Retinopathy(DR), Artificial Intelligence,Machine-learning, Deep-learning, Deep Neural Network

"A Review on Deep Convolutional Neural Networks for Diabetic Retinopathy Detection by Image Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 11, page no.d768-d773, November-2022, Available :http://www.jetir.org/papers/JETIR2211404.pdf

"A Review on Deep Convolutional Neural Networks for Diabetic Retinopathy Detection by Image Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 11, page no. ppd768-d773, November-2022, Available at : http://www.jetir.org/papers/JETIR2211404.pdf