Self-supervised vision transformers for intelligent OCT-based retinal disease classification and severity assessment
A computational intelligence framework is proposed that combines the DINO self-supervised learning method with Vision Transformers to learn robust feature representations from unlabeled optical coherence tomography (OCT) scans and demonstrates that SSL-based models can effectively learn informative features from unlabe...