David Charte

22 papers Misc 2Journal 19Unranked 1
YearRankTypeTitle / Venue / Authors
2022 J jnl
A tutorial on the segmentation of metallographic images: Taxonomy, new MetalDAM dataset, deep learning-based ensemble model, experimental analysis and challenges.
Inf. Fusion
Julián Luengo, Raúl Moreno, Iván Sevillano-García, David Charte, Adrián Peláez-Vegas, Marta Fernández-Moreno, Pablo Mesejo, Francisco Herrera
2022 J jnl
Reducing Data Complexity Using Autoencoders With Class-Informed Loss Functions.
IEEE Trans. Pattern Anal. Mach. Intell.
David Charte, Francisco Charte, Francisco Herrera
2021 J jnl
Reducing Data Complexity using Autoencoders with Class-informed Loss Functions.
CoRR
David Charte, Francisco Charte, Francisco Herrera
2021 J jnl
Revisiting data complexity metrics based on morphology for overlap and imbalance: snapshot, new overlap number of balls metrics and singular problems prospect.
Knowl. Inf. Syst.
José Daniel Pascual-Triana, David Charte, Marta Andrés Arroyo, Alberto Fernández, Francisco Herrera
2021 Misc conf
Slicer: Feature Learning for Class Separability with Least-Squares Support Vector Machine Loss and COVID-19 Chest X-Ray Case Study.
HAIS
David Charte, Iván Sevillano-García, María Jesús Lucena-González, José Luis Martín-Rodríguez, Francisco Charte, Francisco Herrera
2020 J jnl
A Showcase of the Use of Autoencoders in Feature Learning Applications.
CoRR
David Charte, Francisco Charte, María José del Jesus, Francisco Herrera
2020 J jnl
An analysis on the use of autoencoders for representation learning: Fundamentals, learning task case studies, explainability and challenges.
Neurocomputing
David Charte, Francisco Charte, María José del Jesus, Francisco Herrera
2020 J jnl
An analysis on the use of autoencoders for representation learning: fundamentals, learning task case studies, explainability and challenges.
CoRR
David Charte, Francisco Charte, María José del Jesus, Francisco Herrera
2020 J jnl
Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications.
Neurocomputing
Juan Manuel Górriz, Javier Ramírez, Andrés Ortiz, Francisco Jesús Martínez-Murcia, Fermín Segovia, John Suckling, Matthew Leming, Yu-Dong Zhang, José Ramón Álvarez Sánchez, Guido Bologna, María Paula Bonomini, Fernando E. Casado, David Charte, Francisco Charte, Ricardo Contreras, Alfredo Cuesta-Infante, Richard J. Duro, Antonio Fernández-Caballero, José Manuel Ferrández
2020 J jnl
COVIDGR Dataset and COVID-SDNet Methodology for Predicting COVID-19 Based on Chest X-Ray Images.
IEEE J. Biomed. Health Informatics
Siham Tabik, Anabel Gómez-Ríos, J. L. Martín-Rodríguez, I. Sevillano-García, Manuel Rey-Area, David Charte, Emilio Guirado, Juan-Luis Suárez, Julián Luengo, M. A. Valero-González, P. García-Villanova, Eulalia Olmedo-Sánchez, Francisco Herrera
2020 J jnl
COVIDGR dataset and COVID-SDNet methodology for predicting COVID-19 based on Chest X-Ray images.
CoRR
Siham Tabik, Anabel Gómez-Ríos, J. L. Martín-Rodríguez, I. Sevillano-García, Manuel Rey-Area, David Charte, Emilio Guirado, Juan-Luis Suárez, Julián Luengo, M. A. Valero-González, P. García-Villanova, Eulalia Olmedo-Sánchez, Francisco Herrera
2020 J jnl
Revisiting Data Complexity Metrics Based on Morphology for Overlap and Imbalance: Snapshot, New Overlap Number of Balls Metrics and Singular Problems Prospect.
CoRR
José Daniel Pascual-Triana, David Charte, Marta Andrés Arroyo, Alberto Fernández, Francisco Herrera
2019 — conf
A Showcase of the Use of Autoencoders in Feature Learning Applications.
IWINAC (2)
David Charte, Francisco Charte, María José del Jesus, Francisco Herrera
2019 J jnl
A snapshot on nonstandard supervised learning problems: taxonomy, relationships, problem transformations and algorithm adaptations.
Prog. Artif. Intell.
David Charte, Francisco Charte, Salvador García, Francisco Herrera
2019 J jnl
Ruta: Implementations of neural autoencoders in R.
Knowl. Based Syst.
David Charte, Francisco Herrera, Francisco Charte
2018 J jnl
A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines.
CoRR
David Charte, Francisco Charte, Salvador García, María José del Jesus, Francisco Herrera
2018 J jnl
A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines.
Inf. Fusion
David Charte, Francisco Charte, Salvador García, María José del Jesus, Francisco Herrera
2018 J jnl
A snapshot on nonstandard supervised learning problems: taxonomy, relationships and methods.
CoRR
David Charte, Francisco Charte, Salvador García, Francisco Herrera
2018 J jnl
Tips, guidelines and tools for managing multi-label datasets: The mldr.datasets R package and the Cometa data repository.
Neurocomputing
Francisco Charte, Antonio J. Rivera, David Charte, María José del Jesus, Francisco Herrera
2018 J jnl
Tips, guidelines and tools for managing multi-label datasets: the mldr.datasets R package and the Cometa data repository.
CoRR
Francisco Charte, Antonio J. Rivera, David Charte, María José del Jesus, Francisco Herrera
2016 Misc conf
R Ultimate Multilabel Dataset Repository.
HAIS
Francisco Charte, David Charte, Antonio J. Rivera, María José del Jesus, Francisco Herrera
2015 J jnl
Working with Multilabel Datasets in R: The mldr Package.
R J.
Francisco Charte, David Charte