Search Results for author: Daniel DeAlcala

Found 5 papers, 1 papers with code

Is my Data in your AI Model? Membership Inference Test with Application to Face Images

no code implementations14 Feb 2024 Daniel DeAlcala, Aythami Morales, Gonzalo Mancera, Julian Fierrez, Ruben Tolosana, Javier Ortega-Garcia

This paper introduces the Membership Inference Test (MINT), a novel approach that aims to empirically assess if specific data was used during the training of Artificial Intelligence (AI) models.

Face Recognition

BeCAPTCHA-Type: Biometric Keystroke Data Generation for Improved Bot Detection

no code implementations27 Jul 2022 Daniel DeAlcala, Aythami Morales, Ruben Tolosana, Alejandro Acien, Julian Fierrez, Santiago Hernandez, Miguel A. Ferrer, Moises Diaz

Different bot detectors are considered based on several supervised classifiers (Support Vector Machine, Random Forest, Gaussian Naive Bayes and a Long Short-Term Memory network) and a learning framework including human and synthetic samples.

Few-Shot Learning Vocal Bursts Type Prediction

ALEBk: Feasibility Study of Attention Level Estimation via Blink Detection applied to e-Learning

no code implementations16 Dec 2021 Roberto Daza, Daniel DeAlcala, Aythami Morales, Ruben Tolosana, Ruth Cobos, Julian Fierrez

The experimental framework is carried out using a public multimodal database for eye blink detection and attention level estimation called mEBAL, which comprises data from 38 students and multiples acquisition sensors, in particular, i) an electroencephalogram (EEG) band which provides the time signals coming from the student's cognitive information, and ii) RGB and NIR cameras to capture the students face gestures.


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

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