3 papers
cs.CV2024
Enhancing the Utility of Privacy-Preserving Cancer Classification using Synthetic Data
Richard Osuala, Daniel M. Lang, Anneliese Riess +6
Deep learning holds immense promise for aiding radiologists in breast cancer detection. However, achieving optimal model performance is hampered by limitations in availability and…
cs.CV2024
Progressive Growing of Patch Size: Resource-Efficient Curriculum Learning for Dense Prediction Tasks
Stefan M. Fischer, Lina Felsner, Richard Osuala +4
In this work, we introduce Progressive Growing of Patch Size, a resource-efficient implicit curriculum learning approach for dense prediction tasks. Our curriculum approach is defi…
eess.IV2023
Revisiting Skin Tone Fairness in Dermatological Lesion Classification
Thorsten Kalb, Kaisar Kushibar, Celia Cintas +3
Addressing fairness in lesion classification from dermatological images is crucial due to variations in how skin diseases manifest across skin tones. However, the absence of skin t…