Retinal Malady Classification using AI: A novel ViT-SVM combination architecture

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Abstract:Macular Holes, Central serous retinopathy and Diabetic Retinopathy are one of the most widespread maladies of the eyes responsible for either partial or complete vision loss, thus making it clear that early detection of the mentioned defects is detrimental for the well-being of the patient. This study intends to introduce the application of Vision Transformer and Support Vector Machine based hybrid architecture (ViT-SVM) and analyse its performance to classify the optical coherence topography (OCT) Scans with the intention to automate the early detection of these retinal defects.

Subjects:

Image and Video Processing (eess.IV); Computer Vision and Pattern Recognition (cs.CV)

Cite as: arXiv:2603.29181 [eess.IV]

(or arXiv:2603.29181v1 [eess.IV] for this version)

https://doi.org/10.48550/arXiv.2603.29181

arXiv-issued DOI via DataCite (pending registration)

Journal reference: 6th International Conference on Computing Methodologies and Communication (ICCMC), Erode, India, 2022, pp. 1659-1664

Related DOI:

https://doi.org/10.1109/ICCMC53470.2022.9753876

DOI(s) linking to related resources

Submission history

From: Shashwat Jha [view email] [v1] Tue, 31 Mar 2026 02:48:28 UTC (608 KB)