Automated Tool Support for Glaucoma Identification With Explainability Using Fundus Images
Automated Tool Support for Glaucoma Identification With Explainability Using Fundus Images is a scholarly work, published in 2024 in ''IEEE Access''. The main subjects of the publication include diabetic retinopathy, artificial intelligence, identification, computer vision, optometry, uterus, glaucoma, and computer science. The study presents state-of-the-art deep learning techniques to segment and classify fundus images to predict glaucoma conditions and applies visualization techniques to explain the results to ease understandability.