• Tarinee Kanwar
• Dr. Avinash Dhole
• Sampada Vishwas Massey

Cataract refers to the opacification of the ocular lens, resulting in a decline in visual acuity. The current systems have undergone training using a limited dataset, resulting in the issue of overfitting. The suggested approach aims to utilise neural network models for the purpose of classifying between a healthy eye and an eye afflicted with cataract. The detection of cataract is facilitated by the utilisation of the Convolutional Neural Network model. The Convolutional Neural Network (CNN) architecture comprises a total of 34 layers. The picture undergoes a series of convolutional and pooling operations in a hierarchical manner. The output is then acquired at the last layer. The suggested approach employs a deep neural network model to identify the presence of cataract in a picture of the eye.

Neural networks, cataract, computer vision, CNN (Convolutional Neural Network), RNN (Recurrent Neural Network)

"CATARACT DETECTION USING DEEP LEARNING ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 9, page no.e608-e615, September-2023, Available :http://www.jetir.org/papers/JETIR2309473.pdf

"CATARACT DETECTION USING DEEP LEARNING ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 9, page no. ppe608-e615, September-2023, Available at : http://www.jetir.org/papers/JETIR2309473.pdf