44 citations · 50 across the 8 of their papers we have counts for
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cs.CV2025
A Framework for Benchmarking Fairness-Utility Trade-offs in Text-to-Image Models via Pareto Frontiers
Marco N. Bochernitsan, Rodrigo C. Barros, Lucas S. Kupssinskü
Achieving fairness in text-to-image generation demands mitigating social biases without compromising visual fidelity, a challenge critical to responsible AI. Current fairness evalu…
cs.CV2023★ 6 cited
Zero-shot performance of the Segment Anything Model (SAM) in 2D medical imaging: A comprehensive evaluation and practical guidelines
Christian Mattjie, Luis Vinicius de Moura, Rafaela Cappelari Ravazio +4
Segmentation in medical imaging is a critical component for the diagnosis, monitoring, and treatment of various diseases and medical conditions. Presently, the medical segmentation…