Search Results for author: Ignacio Serna

Found 10 papers, 4 papers with code

FaceQgen: Semi-Supervised Deep Learning for Face Image Quality Assessment

1 code implementation3 Jan 2022 Javier Hernandez-Ortega, Julian Fierrez, Ignacio Serna, Aythami Morales

This comparison shows that, even though FaceQgen does not surpass the best existing face quality assessment methods in terms of face recognition accuracy prediction, it achieves good enough results to demonstrate the potential of semi-supervised learning approaches for quality estimation (in particular, data-driven learning based on a single high quality image per subject), having the capacity to improve its performance in the future with adequate refinement of the model and the significant advantage over competing methods of not needing quality labels for its development.

Face Recognition Image Quality Assessment +2

OTB-morph: One-Time Biometrics via Morphing applied to Face Templates

no code implementations25 Nov 2021 Mahdi Ghafourian, Julian Fierrez, Ruben Vera-Rodriguez, Ignacio Serna, Aythami Morales

Cancelable biometrics refers to a group of techniques in which the biometric inputs are transformed intentionally using a key before processing or storage.

IFBiD: Inference-Free Bias Detection

1 code implementation9 Sep 2021 Ignacio Serna, Daniel DeAlcala, Aythami Morales, Julian Fierrez, Javier Ortega-Garcia

This paper is the first to explore an automatic way to detect bias in deep convolutional neural networks by simply looking at their weights.

Bias Detection

SetMargin Loss applied to Deep Keystroke Biometrics with Circle Packing Interpretation

no code implementations2 Sep 2021 Aythami Morales, Julian Fierrez, Alejandro Acien, Ruben Tolosana, Ignacio Serna

This work presents a new deep learning approach for keystroke biometrics based on a novel Distance Metric Learning method (DML).

Metric Learning

Facial Expressions as a Vulnerability in Face Recognition

no code implementations17 Nov 2020 Alejandro Peña, Ignacio Serna, Aythami Morales, Julian Fierrez, Agata Lapedriza

This work explores facial expression bias as a security vulnerability of face recognition systems.

Face Recognition

FairCVtest Demo: Understanding Bias in Multimodal Learning with a Testbed in Fair Automatic Recruitment

no code implementations12 Sep 2020 Alejandro Peña, Ignacio Serna, Aythami Morales, Julian Fierrez

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 demonstrator experiments over an automated recruitment testbed based on Curriculum Vitae: FairCVtest.

Decision Making

Bias in Multimodal AI: Testbed for Fair Automatic Recruitment

1 code implementation15 Apr 2020 Alejandro Peña, Ignacio Serna, Aythami Morales, Julian Fierrez

With the aim of studying how current multimodal algorithms based on heterogeneous sources of information are affected by sensitive elements and inner biases in the data, we propose a fictitious automated recruitment testbed: FairCVtest.

Decision Making Person Recognition

InsideBias: Measuring Bias in Deep Networks and Application to Face Gender Biometrics

no code implementations14 Apr 2020 Ignacio Serna, Alejandro Peña, Aythami Morales, Julian Fierrez

We analyze how bias affects deep learning processes through a toy example using the MNIST database and a case study in gender detection from face images.

Bias Detection

Algorithmic Discrimination: Formulation and Exploration in Deep Learning-based Face Biometrics

1 code implementation4 Dec 2019 Ignacio Serna, Aythami Morales, Julian Fierrez, Manuel Cebrian, Nick Obradovich, Iyad Rahwan

We experimentally show that demographic groups highly represented in popular face databases have led to popular pre-trained deep face models presenting strong algorithmic discrimination.

Face Recognition

Cannot find the paper you are looking for? You can Submit a new open access paper.