Publications

A tutorial on the segmentation of metallographic images: Taxonomy, new MetalDAM dataset, deep learning-based ensemble model, experimental analysis and challenges
Julián Luengo, Raúl Moreno, Iván Sevillano García, David Charte, et al. Information Fusion.

Revisiting data complexity metrics based on morphology for overlap and imbalance: snapshot, new overlap number of balls metrics and singular problems prospect
Jose Daniel Pascual Triana, David Charte, Marta Andrés Arroyo, Alberto Fernández, Francisco Herrera. Knowledge and Information Systems.

Slicer: Feature Learning for Class Separability with Least-Squares Support Vector Machine Loss and COVID-19 Chest X-Ray Case Study
David Charte, Iván Sevillano García, María Jesús Lucena González, et al. International Conference on Hybrid Artificial Intelligence Systems.

Reducing Data Complexity using Autoencoders with Class-informed Loss Functions
David Charte, Francisco Charte, Francisco Herrera. IEEE Transactions on Pattern Analysis and Machine Intelligence.

Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications
Juan M. Górriz, et al. Neurocomputing.

COVIDGR Dataset and COVID-SDNet Methodology for Predicting COVID-19 Based on Chest X-Ray Images
Siham Tabik, Anabel Gómez Ríos, José Luis Martín Rodríguez, et al. IEEE Journal of Biomedical and Health Informatics.

An analysis on the use of autoencoders for representation learning: Fundamentals, learning task case studies, explainability and challenges
David Charte, Francisco Charte, María José del Jesus, Francisco Herrera. Neurocomputing.

A snapshot on nonstandard supervised learning problems: taxonomy, relationships, problem transformations and algorithm adaptations
David Charte, Francisco Charte, Salvador García, Francisco Herrera. Progress in Artificial Intelligence.

A showcase of the use of autoencoders in feature learning applications
David Charte, Francisco Charte, María José del Jesus, Francisco Herrera. International Work-Conference on the Interplay Between Natural and Artificial Computation.

Ruta: Implementations of neural autoencoders in R
David Charte, Francisco Herrera, Francisco Charte. Knowledge-Based Systems.

A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines
David Charte, Francisco Charte, Salvador García, María José del Jesus, Francisco Herrera. Information Fusion.

Tips, guidelines and tools for managing multi-label datasets: The mldr.datasets R package and the Cometa data repository
Francisco Charte, Antonio Rivera, David Charte, María José del Jesus, Francisco Herrera. Neurocomputing.

R ultimate multilabel dataset repository
Francisco Charte, David Charte, Antonio Rivera, et al. International conference on hybrid artificial intelligence systems.

Working with Multilabel Datasets in R: The mldr Package
Francisco Charte, David Charte. R Journal.