3 citations · 6 across the 3 of their papers we have counts for
8 papers · 1 filter
FaceQgen: Semi-Supervised Deep Learning for Face Image Quality Assessment
Javier Hernandez-Ortega, Julian Fierrez, Ignacio Serna +1
In this paper we develop FaceQgen, a No-Reference Quality Assessment approach for face images based on a Generative Adversarial Network that generates a scalar quality measure rela…
SetMargin Loss applied to Deep Keystroke Biometrics with Circle Packing Interpretation
Aythami Morales, Julian Fierrez, Alejandro Acien +2
This work presents a new deep learning approach for keystroke biometrics based on a novel Distance Metric Learning method (DML). DML maps input data into a learned representation s…
Facial Expressions as a Vulnerability in Face Recognition
Alejandro Peña, Ignacio Serna, Aythami Morales +2
This work explores facial expression bias as a security vulnerability of face recognition systems. Despite the great performance achieved by state-of-the-art face recognition syste…
FairCVtest Demo: Understanding Bias in Multimodal Learning with a Testbed in Fair Automatic Recruitment
Alejandro Peña, Ignacio Serna, Aythami Morales +1
With the aim of studying how current multimodal AI algorithms based on heterogeneous sources of information are affected by sensitive elements and inner biases in the data, this de…
Bias in Multimodal AI: Testbed for Fair Automatic Recruitment
Alejandro Peña, Ignacio Serna, Aythami Morales +1
The presence of decision-making algorithms in society is rapidly increasing nowadays, while concerns about their transparency and the possibility of these algorithms becoming new s…
SensitiveLoss: Improving Accuracy and Fairness of Face Representations with Discrimination-Aware Deep Learning
Ignacio Serna, Aythami Morales, Julian Fierrez +3
We propose a discrimination-aware learning method to improve both accuracy and fairness of biased face recognition algorithms. The most popular face recognition benchmarks assume a…