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Author

D. Iakovidis

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Conference Open access Sep 2026

Self-Supervised Perceptually Interpretable Monocular Depth Estimation

Self-supervised monocular depth estimation (MDE) enables depth prediction from monocular images without requiring ground-truth supervision, making it attractive for large-scale and real-world applications. Despite steady improvements in accuracy, most existing methods remain difficult to interpret, as depth is inferred...

Zainol Abidin, George Dimas, D. Iakovidis · 0 citations
Preprint Sep 2026

Confidence-Aware Teacher-Student Distillation for 3D Medical Segmentation

Medical image segmentation models typically rely on large amounts of densely annotated volumetric data, limiting their scalability across tasks and imaging modalities. This work addresses the challenge of predicting entire 3D anatomical structures from extreme annotation sparsity. An annotation-efficient student-teache...

Georgios Triantafyllou, D. Iakovidis · 0 citations

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