Cataract Eye Detection Using Deep Learning Based Feature Extraction with Classification

Abstract

More over 50% of blindness in the industrialised world is caused by cataracts, making them one of the most common causes of blindness. This research aims to design earlier cataract detection using machine learning technique. Here the dataset has been collected through the IOT module from the public health dataset. This data has been pre-processed, and then the data has been pre-trained for better data classification using K- NEURAL NETWORKS (K-NeuNet). By this pre-trained data the detection has been carried out, when the image detected with symptoms of cataract eye, the data has been classified using deep region neural networks (De-RegNN) to detect and grad cataract automatically. The simulation results show optimal accuracy, precision, recall, F-1 score and specificity. It uses regular eye images to detect cataracts.