An Attention Infused Deep Learning System with Grad-CAM Visualization for Early Screening of Glaucoma

Abstract: This research work reveals the eye opening wisdom of the hybrid labyrinthine deep learning models synergy born out of combining a trailblazing convolutional neural network with a disruptive Vision Transformer, both intertwined together with a radical Cross Attention module. Here, two high yielding datasets for artificial intelligence models in detecting glaucoma, namely ACRIMA and Drishti, are utilized.