A Deep Learning Model for Neural Network Optimization for Glaucoma Classification Using Fundus and Oct Feature Fusion
Nanditha Krishna, Nagamani K
Abstract:Irreversible vision loss is a common consequence of glaucoma, demands accurate and timely diagnosis for effective management. This research aims to enhance glaucoma classification accuracy by fusing information from two distinct imaging modalities like using deep learning explores the fusion of these modalities through an innovative neural network architecture with optimization. This approach combines Deep Stochastic Variational Autoencoder Convolution Neural Networks (DSVAECNN) and Adam optimization technique… Show more
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