Daniel Paternain
YOU?
Author Swipe
View article: Few-shot multi-token DreamBooth with LoRa for style-consistent character generation
Few-shot multi-token DreamBooth with LoRa for style-consistent character generation Open
The audiovisual industry is undergoing a profound transformation as it is integrating AI developments not only to automate routine tasks but also to inspire new forms of art. This paper addresses the problem of producing a virtually unlimi…
View article: Speeding-up diffusion models for remote sensing semantic segmentation
Speeding-up diffusion models for remote sensing semantic segmentation Open
Denoising Diffusion Probabilistic Models (DDPMs) have demonstrated exceptional potential across various generative modeling tasks. Despite evident promise in semantic segmentation, their adoption for remote sensing remains limited primaril…
View article: A Comparative Study of CO2 Forecasting Strategies in School Classrooms: A Step Toward Improving Indoor Air Quality
A Comparative Study of CO2 Forecasting Strategies in School Classrooms: A Step Toward Improving Indoor Air Quality Open
This paper comprehensively investigates the performance of various strategies for predicting CO2 levels in school classrooms over different time horizons by using data collected through IoT devices. We gathered Indoor Air Quality (IAQ) dat…
View article: Biased Heritage: How Datasets Shape Models in Facial Expression Recognition
Biased Heritage: How Datasets Shape Models in Facial Expression Recognition Open
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 based on protected characteristics such as gender, race, or…
View article: Metrics for Dataset Demographic Bias: A Case Study on Facial Expression Recognition
Metrics for Dataset Demographic Bias: A Case Study on Facial Expression Recognition Open
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 types of demographic bias are statistical imbalances in th…
View article: DSAP: Analyzing Bias Through Demographic Comparison of Datasets
DSAP: Analyzing Bias Through Demographic Comparison of Datasets Open
In the last few years, Artificial Intelligence systems have become increasingly widespread. Unfortunately, these systems can share many biases with human decision-making, including demographic biases. Often, these biases can be traced back…
View article: Metrics for Dataset Demographic Bias: A Case Study on Facial Expression Recognition
Metrics for Dataset Demographic Bias: A Case Study on Facial Expression Recognition Open
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 types of demographic bias are statistical imbalances in th…
View article: A supervised fuzzy measure learning algorithm for combining classifiers
A supervised fuzzy measure learning algorithm for combining classifiers Open
Fuzzy measure-based aggregations allow taking interactions among coalitions of the input sources into account. Their main drawback when applying them in real-world problems, such as combining classifier ensembles, is how to define the fuzz…
View article: Gender Stereotyping Impact in Facial Expression Recognition
Gender Stereotyping Impact in Facial Expression Recognition Open
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. Unfortunately, as the images naturally integrate some demographic i…
View article: Assessing Demographic Bias Transfer from Dataset to Model: A Case Study in Facial Expression Recognition
Assessing Demographic Bias Transfer from Dataset to Model: A Case Study in Facial Expression Recognition Open
The increasing amount of applications of Artificial Intelligence (AI) has led researchers to study the social impact of these technologies and evaluate their fairness. Unfortunately, current fairness metrics are hard to apply in multi-clas…
View article: A Study of OWA Operators Learned in Convolutional Neural Networks
A Study of OWA Operators Learned in Convolutional Neural Networks Open
Ordered Weighted Averaging (OWA) operators have been integrated in Convolutional Neural Networks (CNNs) for image classification through the OWA layer. This layer lets the CNN integrate global information about the image in the early stage…
View article: Issue Information
Issue Information Open
explores several fascinating editorials written by today's experts in the fi eld.Because new developments are being introduced each day, there's much to be learned-examination, analysis creation, information retrieval, man-computer interac…
View article: Some preference involved aggregation models for basic uncertain information using uncertainty transformation
Some preference involved aggregation models for basic uncertain information using uncertainty transformation Open
In decision making, very often the data collected are with different extents of uncertainty. The recently introduced concept, Basic Uncertain Information (BUI), serves as one ideal information representation to well model involved uncertai…
View article: Unsupervised Fuzzy Measure Learning for Classifier Ensembles From Coalitions Performance
Unsupervised Fuzzy Measure Learning for Classifier Ensembles From Coalitions Performance Open
In Machine Learning an ensemble refers to the combination of several classifiers with the objective of improving the performance of every one of its counterparts. To design an ensemble two main aspects must be considered: how to create a d…
View article: OWA Operators Based on Admissible Permutations
OWA Operators Based on Admissible Permutations Open
In this work we propose a new OWA operator defined on bounded convex posets of a vector-lattice. In order to overcome the non-existence of a total order, which is necessary to obtain a non-decreasing arrangement of the input data, we use t…
View article: Some Characterizations of Lattice OWA Operators
Some Characterizations of Lattice OWA Operators Open
Ordered Weighted Averaging (OWA) operators are a family of aggregation functions for data fusion. If the data are real numbers, then OWA operators can be characterized either as a special kind of discrete Choquet integral or simply as an a…
View article: Some properties of lattice OWA operators and their importance in image processing
Some properties of lattice OWA operators and their importance in image processing Open
In this work we deal with the problem of using OWA operators in color image reduction algorithms.For this reason, we study OWA operators defined on an arbitrary finite lattice endowed with a t-norm and a t-conorm.In the case of RGB color i…