Homa Rashidisabet

Improving Generalization of Deep Learning for Glaucoma Classification Under Real-World Domain Shift via Unsupervised Domain Adaptation

The proposed UDA framework improves cross-domain generalizability of DL-based glaucoma classification from fundus images and exhibits feature utilization patterns more aligned with an ideal baseline, reducing overreliance on optic nerve head–specific cues and supporting more robust decision-making under domain shift.