COMUNICACIÓN Y DIVULGACIÓN CIENTÍFICA

Francisco Charte Ojeda

Universidad de Jaén

Publicaciones

MORENA: Empty Images Detection Based on Unsupervised Reconstruction Error Analysis

2026
book-chapter

10.1007/978-3-032-02725-2_44

DESReg: Dynamic Ensemble Selection library for Regression tasks

Neurocomputing

2024
journal-article

10.1016/j.neucom.2024.127487

Analysis of Transformer Model Applications

2023
book-chapter

10.1007/978-3-031-40725-3_20

mldr.resampling: Efficient reference implementations of multilabel resampling algorithms

AUTHORS: Antonio J. Rivera; Miguel A. Dávila; D. Elizondo; María J. del Jesus; Francisco Charte

Neurocomputing

2023
journal-article

10.1016/j.neucom.2023.126806

NOSpcimen: A First Approach to Unsupervised Discarding of Empty Photo Trap Images

2023
book-chapter

10.1007/978-3-031-43078-7_4

Low-cost IoT gas concentrator system prototype

AUTHORS: Alicia Montoro-Lendinez; Jose Luis Lopez-Ruiz; F. Charte; Macarena Espinilla-Estevez; Javier Medina-Quero

2022
conference-paper

10.1109/TAEE54169.2022.9840592

Reducing Data Complexity Using Autoencoders With Class-Informed Loss Functions

AUTHORS: David Charte; Francisco Charte; Francisco Herrera

IEEE Transactions on Pattern Analysis and Machine Intelligence

2022
journal-article

10.1109/TPAMI.2021.3127698

Slicer: Feature Learning for Class Separability with Least-Squares Support Vector Machine Loss and COVID-19 Chest X-Ray Case Study

AUTHORS: David Charte; Iván Sevillano-García; María Jesús Lucena-González; José Luis Martín-Rodríguez; Francisco Charte; Francisco Herrera

2021
book-chapter

10.1007/978-3-030-86271-8_26

A Comprehensive and Didactic Review on Multilabel Learning Software Tools

AUTHORS: Francisco Charte

IEEE Access

2020
journal-article

10.1109/ACCESS.2020.2979787

An analysis on the use of autoencoders for representation learning: Fundamentals, learning task case studies, explainability and challenges

AUTHORS: David Charte; Francisco Charte; María J. del Jesus; Francisco Herrera

Neurocomputing

2020
journal-article

10.1016/j.neucom.2020.04.057

Choosing the proper autoencoder for feature fusion based on data complexity and classifiers: Analysis, tips and guidelines

Information Fusion

2020
journal-article

10.1016/j.inffus.2019.07.004

A Showcase of the Use of Autoencoders in Feature Learning Applications

AUTHORS: David Charte; Francisco Charte; María J. del Jesus; Francisco Herrera

2019
book-chapter

10.1007/978-3-030-19651-6_40

A snapshot on nonstandard supervised learning problems: taxonomy, relationships, problem transformations and algorithm adaptations

AUTHORS: Charte, D.; Charte, F.; García, S.; Herrera, F.

Progress in Artificial Intelligence

2019
journal-article

10.1007/s13748-018-00167-7

Automatic Time Series Forecasting with GRNN: A Comparison with Other Models

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2019
book-chapter

10.1007/978-3-030-20521-8_17

Automating Autoencoder Architecture Configuration: An Evolutionary Approach

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2019
book-chapter

10.1007/978-3-030-19591-5_35

Dealing with difficult minority labels in imbalanced mutilabel data sets

Neurocomputing

2019
journal-article

10.1016/j.neucom.2016.08.158

predtoolsTS: R package for streamlining time series forecasting

Progress in Artificial Intelligence

2019
journal-article

10.1007/s13748-019-00193-z

REMEDIAL-HwR: Tackling multilabel imbalance through label decoupling and data resampling hybridization

Neurocomputing

2019
journal-article

10.1016/j.neucom.2017.01.118

Ruta: Implementations of neural autoencoders in R

AUTHORS: Charte, D.; Herrera, F.; Charte, F.

Knowledge-Based Systems

2019
journal-article

10.1016/j.knosys.2019.01.014

Smartdata: Data preprocessing to achieve smart data in R

AUTHORS: Ignacio Cordón; Julián Luengo; Salvador García; Francisco Herrera; Francisco Charte

Neurocomputing

2019
journal-article

10.1016/j.neucom.2019.06.006

A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines

AUTHORS: Charte, D.; Charte, F.; García, S.; del Jesus, M.J.; Herrera, F.

Information Fusion

2018
journal-article

10.1016/j.inffus.2017.12.007

AEkNN: An autoencoder kNN–based classifier with built-in dimensionality reduction

International Journal of Computational Intelligence Systems

2018
journal-article

10.2991/ijcis.2018.125905686

Tips, guidelines and tools for managing multi-label datasets: The mldr.datasets R package and the Cometa data repository

Neurocomputing

2018
journal-article

10.1016/j.neucom.2018.02.011

A first approach towards a fuzzy decision tree for multilabel classification

AUTHORS: Prati, R.C.; Charte, F.; Herrera, F.

IEEE International Conference on Fuzzy Systems

2017
conference-paper

10.1109/FUZZ-IEEE.2017.8015521

Comparative analysis of data mining and response surface methodology predictive models for enzymatic hydrolysis of pretreated olive tree biomass

Computers and Chemical Engineering

2017
journal-article

10.1016/j.compchemeng.2017.02.008

Is the average photon energy a unique characteristic of the spectral distribution of global irradiance?

AUTHORS: Nofuentes, G.; Gueymard, C.A.; Aguilera, J.; Pérez-Godoy, M.D.; Charte, F.

Solar Energy

2017
journal-article

10.1016/j.solener.2017.03.086

Subgroup discovery with evolutionary fuzzy systems in r: The SDEFSR package

AUTHORS: García, A.M.; Charte, F.; González, P.; Carmona, C.J.; del Jesus, M.J.

R Journal

2016
journal-article

Addressing imbalance in multilabel classification: Measures and random resampling algorithms

Neurocomputing

2015
journal-article

10.1016/j.neucom.2014.08.091

MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation

Knowledge-Based Systems

2015
journal-article

10.1016/j.knosys.2015.07.019

QUINTA: A question tagging assistant to improve the answering ratio in electronic forums

Proceedings - EUROCON 2015

2015
conference-paper

10.1109/EUROCON.2015.7313677

Resampling multilabel datasets by decoupling highly imbalanced labels

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

2015
conference-paper

10.1007/978-3-319-19644-2_41

Working with multilabel datasets in R: The mldr package

AUTHORS: Charte, F.; Charte, D.

R Journal

2015
journal-article

Concurrence among imbalanced labels and its influence on multilabel resampling algorithms

Hybrid Artificial Intelligence Systems

2014
other

10.1007/978-3-319-07617-1_10

LI-MLC: A label inference methodology for addressing high dimensionality in the label space for multilabel classification

IEEE Trans. Neural Netw. Learning Syst.

2014
journal-article

10.1109/tnnls.2013.2296501

MLeNN: A first approach to heuristic multilabel undersampling

Intelligent Data Engineering and Automated Learning – IDEAL 2014

2014
other

10.1007/978-3-319-10840-7_1

Propuesta de una asignatura de Diseño de Servidores para la especialidad de Tecnologías de Información

2014
magazine-article

A first approach to deal with imbalance in multi-label datasets

2013
other

10.1007/978-3-642-40846-5_16

Alternative OVA Proposals for Cooperative Competitive RBFN Design in Classification Tasks

2013
other

10.1007/978-3-642-38679-4_32

Improving multi-label classifiers via label reduction with association rules

2012
other

10.1007/978-3-642-28931-6_18

Multi-label testing for CO²RBFN: A first approach to the problem transformation methodology for multi-label classification

11th International Work-Conference on Artificial Neural Networks, IWANN 2011

2011
other

10.1007/978-3-642-21501-8_6

ReturnOK, LA Wiki sobre retroinformática

Iniciación a la Investigación

2011
book-chapter

Conocemos Google Android

PC Actual. Personal computer

2009
journal-article

CUDA, revolución en desarrollo

PC Actual. Personal computer

2009
journal-article

NetBeans, un entorno polifacético

PC Actual. Personal computer

2009
journal-article

Adobe AIR

PC Actual. Personal computer

2008
journal-article

Cálculos estadísticos con Excel

2008
journal-article

Entorno de desarrollo. Libre y multiplataforma. MonoDevelop versión 1.0.

PC Actual. Personal computer

2008
journal-article

Software. Microsoft Visual Studio Team System 2008. Ultima versión de Visual Studio. Un sistema muy flexible.

PC Actual. Personal computer

2008
journal-article

Software. SQL Server 2008. Renovada gestión de datos.

PC Actual. Personal computer

2008
journal-article

Trucos para un PC más seguro: Las técnicas de programación más seguras.

PC Actual. Personal computer

2008
journal-article

AJAX (última entrega)

PC Actual. Personal computer

2007
journal-article

Pc práctico. Visual Studio Orcas. Un entorno de desarrollo futuro.

PC Actual. Personal computer

2007
journal-article

Software. Microsoft. NET Framework 3.0. La API de Windows Vista.

PC Actual. Personal computer

2007
journal-article

Visual Studio 2008 Beta 2

Sólo programadores

2007
journal-article

Software: Plataforma. NET 2.0 (y III)

PC Actual. Personal computer

2006
journal-article

Visual Studio 2005 ediciones Express (I)

Sólo programadores

2006
journal-article

Visual Studio 2005 ediciones Express (II)

Sólo programadores

2006
journal-article

Visual Studio 2005 ediciones Express (y III)

Sólo programadores

2006
manual

Acceso a datos

Sólo programadores

2005
journal-article

Borland JBuilder 9

PC Actual. Personal computer

2005
journal-article

Programación, desarrollo con JBuilder 2005, el entorno de desarrollo Java más polifacético y extendido se pone al d’ia

PC Actual. Personal computer

2005
journal-article

Borland c# Builder 1.0

Sólo programadores

2004
journal-article

Curso de ASP. NET

Sólo programadores

2004
manual

Dossier: Curso ASP. NET

Sólo programadores

2004
manual

J2SE 5.0, La mayor renovación del lenguaje Java

PC Actual. Personal computer

2004
journal-article

Novedades en C# 2.0 (y II)

Sólo programadores

2004
journal-article

Suites de seguridad

PC Actual. Personal computer

2004
journal-article

Visual Studio 2005 CTP March 2004 (y II)

Sólo programadores

2004
journal-article

Bases de datos

PC Actual. Personal computer

2003
journal-article

PHP 5 beta 1

PC Actual. Personal computer

2003
journal-article

Visual FoxPro 8

PC Actual. Personal computer

2003
journal-article

Visual Studio. Net

PC Actual. Personal computer

2003
journal-article

Contacto

fcharte@ujaen.es

Francisco Charte Ojeda

Publicaciones

MORENA: Empty Images Detection Based on Unsupervised Reconstruction Error Analysis

DESReg: Dynamic Ensemble Selection library for Regression tasks

Analysis of Transformer Model Applications

mldr.resampling: Efficient reference implementations of multilabel resampling algorithms

NOSpcimen: A First Approach to Unsupervised Discarding of Empty Photo Trap Images

Low-cost IoT gas concentrator system prototype

Reducing Data Complexity Using Autoencoders With Class-Informed Loss Functions

Slicer: Feature Learning for Class Separability with Least-Squares Support Vector Machine Loss and COVID-19 Chest X-Ray Case Study

A Comprehensive and Didactic Review on Multilabel Learning Software Tools

An analysis on the use of autoencoders for representation learning: Fundamentals, learning task case studies, explainability and challenges

Choosing the proper autoencoder for feature fusion based on data complexity and classifiers: Analysis, tips and guidelines

A Showcase of the Use of Autoencoders in Feature Learning Applications

A snapshot on nonstandard supervised learning problems: taxonomy, relationships, problem transformations and algorithm adaptations

Automatic Time Series Forecasting with GRNN: A Comparison with Other Models

Automating Autoencoder Architecture Configuration: An Evolutionary Approach

Dealing with difficult minority labels in imbalanced mutilabel data sets

predtoolsTS: R package for streamlining time series forecasting

REMEDIAL-HwR: Tackling multilabel imbalance through label decoupling and data resampling hybridization

Ruta: Implementations of neural autoencoders in R

Smartdata: Data preprocessing to achieve smart data in R

A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines

AEkNN: An autoencoder kNN–based classifier with built-in dimensionality reduction

Tips, guidelines and tools for managing multi-label datasets: The mldr.datasets R package and the Cometa data repository

A first approach towards a fuzzy decision tree for multilabel classification

Comparative analysis of data mining and response surface methodology predictive models for enzymatic hydrolysis of pretreated olive tree biomass

Is the average photon energy a unique characteristic of the spectral distribution of global irradiance?

Subgroup discovery with evolutionary fuzzy systems in r: The SDEFSR package

Addressing imbalance in multilabel classification: Measures and random resampling algorithms

MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation

QUINTA: A question tagging assistant to improve the answering ratio in electronic forums

Resampling multilabel datasets by decoupling highly imbalanced labels

Working with multilabel datasets in R: The mldr package

Concurrence among imbalanced labels and its influence on multilabel resampling algorithms

LI-MLC: A label inference methodology for addressing high dimensionality in the label space for multilabel classification

MLeNN: A first approach to heuristic multilabel undersampling

Propuesta de una asignatura de Diseño de Servidores para la especialidad de Tecnologías de Información

A first approach to deal with imbalance in multi-label datasets

Alternative OVA Proposals for Cooperative Competitive RBFN Design in Classification Tasks

Improving multi-label classifiers via label reduction with association rules

Multi-label testing for CO2RBFN: A first approach to the problem transformation methodology for multi-label classification

ReturnOK, LA Wiki sobre retroinformática

Conocemos Google Android

CUDA, revolución en desarrollo

NetBeans, un entorno polifacético

Adobe AIR

Cálculos estadísticos con Excel

Entorno de desarrollo. Libre y multiplataforma. MonoDevelop versión 1.0.

Software. Microsoft Visual Studio Team System 2008. Ultima versión de Visual Studio. Un sistema muy flexible.

Software. SQL Server 2008. Renovada gestión de datos.

Trucos para un PC más seguro: Las técnicas de programación más seguras.

AJAX (última entrega)

Pc práctico. Visual Studio Orcas. Un entorno de desarrollo futuro.

Software. Microsoft. NET Framework 3.0. La API de Windows Vista.

Visual Studio 2008 Beta 2

Software: Plataforma. NET 2.0 (y III)

Visual Studio 2005 ediciones Express (I)

Visual Studio 2005 ediciones Express (II)

Visual Studio 2005 ediciones Express (y III)

Acceso a datos

Borland JBuilder 9

Programación, desarrollo con JBuilder 2005, el entorno de desarrollo Java más polifacético y extendido se pone al d’ia

Borland c# Builder 1.0

Curso de ASP. NET

Dossier: Curso ASP. NET

J2SE 5.0, La mayor renovación del lenguaje Java

Novedades en C# 2.0 (y II)

Suites de seguridad

Visual Studio 2005 CTP March 2004 (y II)

Bases de datos

PHP 5 beta 1

Visual FoxPro 8

Visual Studio. Net

Multi-label testing for CO²RBFN: A first approach to the problem transformation methodology for multi-label classification