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cs.CV2025
Weight Space Correlation Analysis: Quantifying Feature Utilization in Deep Learning Models
Chun Kit Wong, Paraskevas Pegios, Nina Weng +4
Deep learning models in medical imaging are susceptible to shortcut learning, relying on confounding metadata (e.g., scanner model) that is often encoded in image embeddings. The c…
cs.CV2024
Learning semantic image quality for fetal ultrasound from noisy ranking annotation
Manxi Lin, Jakob Ambsdorf, Emilie Pi Fogtmann Sejer +9
We introduce the notion of semantic image quality for applications where image quality relies on semantic requirements. Working in fetal ultrasound, where ranking is challenging an…