Abstract
This research paper focuses on building an accurate deep learning model to facilitate glaucoma detection. The document explains the approach used to detect glaucoma in retinal eye scans. The results of this research open the way to the widespread use of this model in the medical fraternity, because we investigated different techniques to solve this problem using different open source and freely available models that were compared. All these templates provide a clear experience to the users who are related to this article. However, the success of these applications also depends on factors such as the quality of retinal scans, the quality of images trained with a deep learning model, etc. The paper concludes with a model that is most suitable for people to create real-time applications in the medical field and improve glaucoma awareness and early detection before it is too late
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