• GANESHKUMAR P

Diabetic retinopathy is a complication of diabetes, caused by high blood sugar levels damaging the back of the eye (retina). It can cause blindness if left undiagnosed and untreated. However, it usually takes several years for diabetic retinopathy to reach a stage where it could threaten your sight. Therefore, computer-based techniques have been developed to identify the disease automatically. Nowadays, detection and classify the diabetic retinopathy diseases is leading research topics. Deep learning, algorithm have recently been used to recognize and categorize various diabetic retinopathy diseases. This article describes a proposed deep learning-based method for detecting and classifying the diabetic retinopathy diseases using a (EN-B7) Efficient Net in (CNN) Convolutional Neural Network. The Proposed method achieves higher accuracy in identifying and classifying the types of diabetic retinopathy diseases than other existing methods. Moreover, it is observed through the result that the proposed approach provides an effective early detection and treatment of (DR) Diabetic Retinopathy diseases when compared to other existing algorithms.

Diabetic retinopathy, Deep learning, Efficient Net, Convolutional Neural Network

"DIAGNOSIS OF DIABETIC RETINOPATHY USING EFFICIEN NET", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.i201-i210, May-2023, Available :http://www.jetir.org/papers/JETIR2305856.pdf

"DIAGNOSIS OF DIABETIC RETINOPATHY USING EFFICIEN NET", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppi201-i210, May-2023, Available at : http://www.jetir.org/papers/JETIR2305856.pdf