2 citations · 7 across the 13 of their papers we have counts for
4 papers · 1 filter
FaceX: Understanding Face Attribute Classifiers through Summary Model Explanations
Ioannis Sarridis, Christos Koutlis, Symeon Papadopoulos +1
EXplainable Artificial Intelligence (XAI) approaches are widely applied for identifying fairness issues in Artificial Intelligence (AI) systems. However, in the context of facial a…
MAVias: Mitigate any Visual Bias
Ioannis Sarridis, Christos Koutlis, Symeon Papadopoulos +1
Mitigating biases in computer vision models is an essential step towards the trustworthiness of artificial intelligence models. Existing bias mitigation methods focus on a small se…
BAdd: Bias Mitigation through Bias Addition
Ioannis Sarridis, Christos Koutlis, Symeon Papadopoulos +1
Computer vision (CV) datasets often exhibit biases that are perpetuated by deep learning models. While recent efforts aim to mitigate these biases and foster fair representations,…
SDFD: Building a Versatile Synthetic Face Image Dataset with Diverse Attributes
Georgia Baltsou, Ioannis Sarridis, Christos Koutlis +1
AI systems rely on extensive training on large datasets to address various tasks. However, image-based systems, particularly those used for demographic attribute prediction, face s…