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cs.CV2025
Biased Heritage: How Datasets Shape Models in Facial Expression Recognition
Iris Dominguez-Catena, Daniel Paternain, Mikel Galar +3
In recent years, the rapid development of artificial intelligence (AI) systems has raised concerns about our ability to ensure their fairness, that is, how to avoid discrimination…
cs.CV2024
Less can be more: representational vs. stereotypical gender bias in facial expression recognition
Iris Dominguez-Catena, Daniel Paternain, Aranzazu Jurio +1
Machine learning models can inherit biases from their training data, leading to discriminatory or inaccurate predictions. This is particularly concerning with the increasing use of…
cs.CV2023
DSAP: Analyzing Bias Through Demographic Comparison of Datasets
Iris Dominguez-Catena, Daniel Paternain, Mikel Galar
In the last few years, Artificial Intelligence systems have become increasingly widespread. Unfortunately, these systems can share many biases with human decision-making, including…