3 citations · 4 across the 5 of their papers we have counts for
5 papers
Privacy-enhancing Sclera Segmentation Benchmarking Competition: SSBC 2025
Matej Vitek, Darian Tomašević, Abhijit Das +32
This paper presents a summary of the 2025 Sclera Segmentation Benchmarking Competition (SSBC), which focused on the development of privacy-preserving sclera-segmentation models tra…
A Multi-Objective Evaluation Framework for Analyzing Utility-Fairness Trade-Offs in Machine Learning Systems
Gökhan Özbulak, Oscar Jimenez-del-Toro, Maíra Fatoretto +2
The evaluation of fairness models in Machine Learning involves complex challenges, such as defining appropriate metrics, balancing trade-offs between utility and fairness, and ther…
Fair Foundation Models for Medical Image Analysis: Challenges and Perspectives
Dilermando Queiroz, Anderson Carlos, André Anjos +1
Ensuring equitable Artificial Intelligence (AI) in healthcare demands systems that make unbiased decisions across all demographic groups, bridging technical innovation with ethical…
Does Data-Efficient Generalization Exacerbate Bias in Foundation Models?
Dilermando Queiroz, Anderson Carlos, Maíra Fatoretto +3
Foundation models have emerged as robust models with label efficiency in diverse domains. In medical imaging, these models contribute to the advancement of medical diagnoses due to…
Using Backbone Foundation Model for Evaluating Fairness in Chest Radiography Without Demographic Data
Dilermando Queiroz, André Anjos, Lilian Berton
Ensuring consistent performance across diverse populations and incorporating fairness into machine learning models are crucial for advancing medical image diagnostics and promoting…