64 citations · 179 across the 10 of their papers we have counts for
12 papers
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…
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…
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…
Metrics for Dataset Demographic Bias: A Case Study on Facial Expression Recognition
Iris Dominguez-Catena, Daniel Paternain, Mikel Galar
Demographic biases in source datasets have been shown as one of the causes of unfairness and discrimination in the predictions of Machine Learning models. One of the most prominent…
Multimodal Parameter-Efficient Few-Shot Class Incremental Learning
Marco D'Alessandro, Alberto Alonso, Enrique Calabrés +1
Few-Shot Class Incremental Learning (FSCIL) is a challenging continual learning task, where limited training examples are available during several learning sessions. To succeed in…
Gender Stereotyping Impact in Facial Expression Recognition
Iris Dominguez-Catena, Daniel Paternain, Mikel Galar
Facial Expression Recognition (FER) uses images of faces to identify the emotional state of users, allowing for a closer interaction between humans and autonomous systems. Unfortun…
Verification system based on long-range iris and Graph Siamese Neural Networks
Francesco Zola, Jose Alvaro Fernandez-Carrasco, Jan Lukas Bruse +2
Biometric systems represent valid solutions in tasks like user authentication and verification, since they are able to analyze physical and behavioural features with high precision…
Assessing Demographic Bias Transfer from Dataset to Model: A Case Study in Facial Expression Recognition
Iris Dominguez-Catena, Daniel Paternain, Mikel Galar
The increasing amount of applications of Artificial Intelligence (AI) has led researchers to study the social impact of these technologies and evaluate their fairness. Unfortunatel…
Generative Adversarial Networks for Bitcoin Data Augmentation
Francesco Zola, Jan Lukas Bruse, Xabier Etxeberria Barrio +2
In Bitcoin entity classification, results are strongly conditioned by the ground-truth dataset, especially when applying supervised machine learning approaches. However, these grou…
Do we still need fuzzy classifiers for Small Data in the Era of Big Data?
Mikel Elkano, Humberto Bustince, Mikel Galar
The Era of Big Data has forced researchers to explore new distributed solutions for building fuzzy classifiers, which often introduce approximation errors or make strong assumption…
On the usage of the probability integral transform to reduce the complexity of multi-way fuzzy decision trees in Big Data classification problems
Mikel Elkano, Mikel Uriz, Humberto Bustince +1
We present a new distributed fuzzy partitioning method to reduce the complexity of multi-way fuzzy decision trees in Big Data classification problems. The proposed algorithm builds…
CFM-BD: a distributed rule induction algorithm for building Compact Fuzzy Models in Big Data classification problems
Mikel Elkano, Jose Sanz, Edurne Barrenechea +2
Interpretability has always been a major concern for fuzzy rule-based classifiers. The usage of human-readable models allows them to explain the reasoning behind their predictions…