Julián Luengo

101 papers A 1B 5C 7Misc 9Journal 67Unranked 10
YearRankTypeTitle / Venue / Authors
2026 J jnl
STOOD-X: Explainable out-of-distribution detection via nonparametric statistical testing on large-scale datasets.
Pattern Recognit.
Iván Sevillano-García, Julián Luengo, Francisco Herrera
2025 J jnl
Developing Big Data anomaly dynamic and static detection algorithms: AnomalyDSD spark package.
Inf. Sci.
Diego García-Gil, David López, Daniel Argüelles-Martino, Jacinto Carrasco, Ignacio Aguilera-Martos, Julián Luengo, Francisco Herrera
2025 J jnl
STOOD-X methodology: using statistical nonparametric test for OOD Detection Large-Scale datasets enhanced with explainability.
CoRR
Iván Sevillano-García, Julián Luengo, Francisco Herrera
2025 J jnl
WinStat: A Family of Trainable Positional Encodings for Transformers in Time Series Forecasting.
Mach. Learn. Knowl. Extr.
Cristhian Moya-Mota, Ignacio Aguilera-Martos, Diego García-Gil, Julián Luengo
2024 J jnl
Combining traditional and spiking neural networks for energy-efficient detection of Eimeria parasites.
Appl. Soft Comput.
Iago Xabier Vázquez, Bahgat Ayasi, Huseyin Seker, Julián Luengo, Javier Sedano, Ángel Miguel García-Vico
2024 J jnl
Local Attention Mechanism: Boosting the Transformer Architecture for Long-Sequence Time Series Forecasting.
CoRR
Ignacio Aguilera-Martos, Andrés Herrera-Poyatos, Julián Luengo, Francisco Herrera
2024 B conf
Local Attention: Enhancing the Transformer Architecture for Efficient Time Series Forecasting.
IJCNN
Ignacio Aguilera-Martos, Andrés Herrera-Poyatos, Julián Luengo, Francisco Herrera
2024 J jnl
SHIELD: A regularization technique for eXplainable Artificial Intelligence.
CoRR
Iván Sevillano-García, Julián Luengo, Francisco Herrera
2023 J jnl
A Survey on Semi-Supervised Semantic Segmentation.
CoRR
Adrián Peláez-Vegas, Pablo Mesejo, Julián Luengo
2023 J jnl
Fusing anomaly detection with false positive mitigation methodology for predictive maintenance under multivariate time series.
Inf. Fusion
David López, Ignacio Aguilera-Martos, Marta García-Bárzana, Francisco Herrera, Diego García-Gil, Julián Luengo
2023 — conf
Low-Impact Feature Reduction Regularization Term: How to Improve Artificial Intelligence with Explainability.
xAI (Late-breaking Work, Demos, Doctoral Consortium)
Iván Sevillano-García, Julián Luengo, Francisco Herrera
2023 J jnl
Multi-step histogram based outlier scores for unsupervised anomaly detection: ArcelorMittal engineering dataset case of study.
Neurocomputing
Ignacio Aguilera-Martos, Marta García-Bárzana, Diego García-Gil, Jacinto Carrasco, David López, Julián Luengo, Francisco Herrera
2023 Misc conf
Optimizing LIME Explanations Using REVEL Metrics.
HAIS
Iván Sevillano-García, Julián Luengo, Francisco Herrera
2023 J jnl
REVEL Framework to Measure Local Linear Explanations for Black-Box Models: Deep Learning Image Classification Case Study.
Int. J. Intell. Syst.
Iván Sevillano-García, Julián Luengo, Francisco Herrera
2023 Misc conf
Revisiting Histogram Based Outlier Scores: Strengths and Weaknesses.
HAIS
Ignacio Aguilera-Martos, Julián Luengo, Francisco Herrera
2023 J jnl
TSFEDL: A python library for time series spatio-temporal feature extraction and prediction using deep learning.
Neurocomputing
Ignacio Aguilera-Martos, Ángel Miguel García-Vico, Julián Luengo, Sergio Damas, Francisco J. Melero, José Javier Valle-Alonso, Francisco Herrera
2022 J jnl
3SHACC: Three stages hybrid agglomerative constrained clustering.
Neurocomputing
Germán González-Almagro, Juan-Luis Suárez, Julián Luengo, José Ramón Cano, Salvador García
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
TSFEDL: A Python Library for Time Series Spatio-Temporal Feature Extraction and Prediction using Deep Learning (with Appendices on Detailed Network Architectures and Experimental Cases of Study).
CoRR
Ignacio Aguilera-Martos, Ángel Miguel García-Vico, Julián Luengo, Sergio Damas, Francisco J. Melero, José Javier Valle-Alonso, Francisco Herrera
2022 J jnl
The impact of heterogeneous distance functions on missing data imputation and classification performance.
Eng. Appl. Artif. Intell.
Miriam Seoane Santos, Pedro Henriques Abreu, Alberto Fernández, Julián Luengo, João A. M. Santos
2021 J jnl
A robust approach for deep neural networks in presence of label noise: relabelling and filtering instances during training.
CoRR
Anabel Gómez-Ríos, Julián Luengo, Francisco Herrera
2021 J jnl
Anomaly Detection in Predictive Maintenance: A New Evaluation Framework for Temporal Unsupervised Anomaly Detection Algorithms.
CoRR
Jacinto Carrasco, Irina Markova, David López, Ignacio Aguilera, Diego García, Marta García-Bárzana, Manuel Arias-Rodil, Julián Luengo, Francisco Herrera
2021 J jnl
Anomaly detection in predictive maintenance: A new evaluation framework for temporal unsupervised anomaly detection algorithms.
Neurocomputing
Jacinto Carrasco, David López, Ignacio Aguilera-Martos, Diego García-Gil, Irina Markova, Marta García-Bárzana, Manuel Arias-Rodil, Julián Luengo, Francisco Herrera
2021 J jnl
Enhancing instance-level constrained clustering through differential evolution.
Appl. Soft Comput.
Germán González-Almagro, Julián Luengo, José Ramón Cano, Salvador García
2021 J jnl
ME-MEOA/DCC: Multiobjective constrained clustering through decomposition-based memetic elitism.
Swarm Evol. Comput.
Germán González-Almagro, Alejandro Rosales-Pérez, Julián Luengo, José Ramón Cano, Salvador García
2021 J jnl
Multiple instance classification: Bag noise filtering for negative instance noise cleaning.
Inf. Sci.
Julián Luengo, Dánel Sánchez Tarragó, Ronaldo C. Prati, Francisco Herrera
2021 J jnl
Synthetic Sample Generation for Label Distribution Learning.
Inf. Sci.
Manuel González, Julián Luengo, José Ramón Cano, Salvador García
2020 Misc conf
Agglomerative Constrained Clustering Through Similarity and Distance Recalculation.
HAIS
Germán González-Almagro, Juan-Luis Suárez, Julián Luengo, José Ramón Cano, Salvador García
2020 — book
Big Data Preprocessing - Enabling Smart Data
Julián Luengo, Diego García-Gil, Sergio Ramírez-Gallego, Salvador García, Francisco Herrera
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
DILS: Constrained clustering through dual iterative local search.
Comput. Oper. Res.
Germán González-Almagro, Julián Luengo, José Ramón Cano, Salvador García
2020 J jnl
Fast and Scalable Approaches to Accelerate the Fuzzy k-Nearest Neighbors Classifier for Big Data.
IEEE Trans. Fuzzy Syst.
Jesús Maillo, Salvador García, Julián Luengo, Francisco Herrera, Isaac Triguero
2020 A conf
Improving constrained clustering via decomposition-based multiobjective optimization with memetic elitism.
GECCO
Germán González-Almagro, Alejandro Rosales-Pérez, Julián Luengo, José Ramón Cano, Salvador García
2020 J jnl
Preprocessing methodology for time series: An industrial world application case study.
Inf. Sci.
Juan Antonio Cortés-Ibáñez, Sergio González, José Javier Valle-Alonso, Julián Luengo, Salvador García, Francisco Herrera
2020 — conf
Similarity-based and Iterative Label Noise Filters for Monotonic Classification.
HICSS
José Ramón Cano, Julián Luengo, Salvador García
2019 C conf
A First Approach on Big Data Missing Values Imputation.
IoTBDS
Besay Montesdeoca, Julián Luengo, Jesús Maillo, Diego García-Gil, Salvador García, Francisco Herrera
2019 C conf
Big Data Preprocessing as the Bridge between Big Data and Smart Data: BigDaPSpark and BigDaPFlink Libraries.
IoTBDS
Diego García-Gil, Alejandro Alcalde-Barros, Julián Luengo, Salvador García, Francisco Herrera
2019 J jnl
Coral species identification with texture or structure images using a two-level classifier based on Convolutional Neural Networks.
Knowl. Based Syst.
Anabel Gómez-Ríos, Siham Tabik, Julián Luengo, A. S. M. Shihavuddin, Francisco Herrera
2019 J jnl
Emerging topics and challenges of learning from noisy data in nonstandard classification: a survey beyond binary class noise.
Knowl. Inf. Syst.
Ronaldo C. Prati, Julián Luengo, Francisco Herrera
2019 J jnl
Enabling Smart Data: Noise filtering in Big Data classification.
Inf. Sci.
Diego García-Gil, Julián Luengo, Salvador García, Francisco Herrera
2019 J jnl
From Big to Smart Data: Iterative ensemble filter for noise filtering in Big Data classification.
Int. J. Intell. Syst.
Diego García-Gil, Francisco Luque Sánchez, Julián Luengo, Salvador García, Francisco Herrera
2019 J jnl
Label noise filtering techniques to improve monotonic classification.
Neurocomputing
José Ramón Cano, Julián Luengo, Salvador García
2019 J jnl
Towards highly accurate coral texture images classification using deep convolutional neural networks and data augmentation.
Expert Syst. Appl.
Anabel Gómez-Ríos, Siham Tabik, Julián Luengo, A. S. M. Shihavuddin, Bartosz Krawczyk, Francisco Herrera
2019 J jnl
Transforming big data into smart data: An insight on the use of the k-nearest neighbors algorithm to obtain quality data.
WIREs Data Mining Knowl. Discov.
Isaac Triguero, Diego García-Gil, Jesús Maillo, Julián Luengo, Salvador García, Francisco Herrera
2018 — conf
A First Study on the Use of Noise Filtering to Clean the Bags in Multi-Instance Classification.
LOPAL
Julián Luengo, Dánel Sánchez Tarragó, Ronaldo C. Prati, Francisco Herrera
2018 B conf
A preliminary study on Hybrid Spill-Tree Fuzzy k-Nearest Neighbors for big data classification.
FUZZ-IEEE
Jesús Maillo, Julián Luengo, Salvador García, Francisco Herrera, Isaac Triguero
2018 J jnl
CNC-NOS: Class noise cleaning by ensemble filtering and noise scoring.
Knowl. Based Syst.
Julián Luengo, Seong-O Shim, Saleh Alshomrani, Abdulrahman H. Altalhi, Francisco Herrera
2018 J jnl
Label Noise Filtering Techniques to Improve Monotonic Classification.
CoRR
José Ramón Cano, Julián Luengo, Salvador García
2018 J jnl
Towards Highly Accurate Coral Texture Images Classification Using Deep Convolutional Neural Networks and Data Augmentation.
CoRR
Anabel Gómez-Ríos, Siham Tabik, Julián Luengo, A. S. M. Shihavuddin, Bartosz Krawczyk, Francisco Herrera
2017 Misc conf
A Study on the Noise Label Influence in Boosting Algorithms: AdaBoost, GBM and XGBoost.
HAIS
Anabel Gómez-Ríos, Julián Luengo, Francisco Herrera
2017 J jnl
Enabling Smart Data: Noise filtering in Big Data classification.
CoRR
Diego García-Gil, Julián Luengo, Salvador García, Francisco Herrera
2017 B conf
Exact fuzzy k-nearest neighbor classification for big datasets.
FUZZ-IEEE
Jesús Maillo, Julián Luengo, Salvador García, Francisco Herrera, Isaac Triguero
2017 J jnl
KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining.
Int. J. Comput. Intell. Syst.
Isaac Triguero, Sergio González, Jose M. Moyano, Salvador García, Jesús Alcalá-Fdez, Julián Luengo, Alberto Fernández, María José del Jesus, Luciano Sánchez, Francisco Herrera
2017 J jnl
The NoiseFiltersR Package: Label Noise Preprocessing in R.
R J.
Pablo Morales-Álvarez, Julián Luengo, Luís Paulo F. Garcia, Ana Carolina Lorena, André C. P. L. F. de Carvalho, Francisco Herrera
2016 Misc conf
A First Study on the Use of Boosting for Class Noise Reparation.
HAIS
Pablo Morales-Alvarez, Julián Luengo, Francisco Herrera
2016 J jnl
Evaluating the classifier behavior with noisy data considering performance and robustness: The Equalized Loss of Accuracy measure.
Neurocomputing
José A. Sáez, Julián Luengo, Francisco Herrera
2016 — conf
From Big Data to Smart Data with the K-Nearest Neighbours Algorithm.
iThings/GreenCom/CPSCom/SmartData
Isaac Triguero, Jesús Maillo, Julián Luengo, Salvador García, Francisco Herrera
2016 J jnl
INFFC: An iterative class noise filter based on the fusion of classifiers with noise sensitivity control.
Inf. Fusion
José A. Sáez, Mikel Galar, Julián Luengo, Francisco Herrera
2016 J jnl
The influence of noise on the evolutionary fuzzy systems for subgroup discovery.
Soft Comput.
Julián Luengo, Ángel Miguel García-Vico, M. Dolores Pérez-Godoy, Cristóbal J. Carmona
2016 J jnl
Tutorial on practical tips of the most influential data preprocessing algorithms in data mining.
Knowl. Based Syst.
Salvador García, Julián Luengo, Francisco Herrera
2015 — conf
A First Approach in the Class Noise Filtering Approaches for Fuzzy Subgroup Discovery.
SOCO
Cristóbal J. Carmona, Julián Luengo
2015 J jnl
An automatic extraction method of the domains of competence for learning classifiers using data complexity measures.
Knowl. Inf. Syst.
Julián Luengo, Francisco Herrera
2015 — book
Data Preprocessing in Data Mining
Salvador García, Julián Luengo, Francisco Herrera
2015 — conf
Naive Bayes Classifier with Mixtures of Polynomials.
ICPRAM (1)
Julián Luengo, Rafael Rumí
2015 J jnl
SMOTE-IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering.
Inf. Sci.
José A. Sáez, Julián Luengo, Jerzy Stefanowski, Francisco Herrera
2015 J jnl
Using the One-vs-One decomposition to improve the performance of class noise filters via an aggregation strategy in multi-class classification problems.
Knowl. Based Syst.
Luís Paulo F. Garcia, José A. Sáez, Julián Luengo, Ana Carolina Lorena, André C. P. L. F. de Carvalho, Francisco Herrera
2014 J jnl
Analyzing the presence of noise in multi-class problems: alleviating its influence with the One-vs-One decomposition.
Knowl. Inf. Syst.
José A. Sáez, Mikel Galar, Julián Luengo, Francisco Herrera
2014 Misc conf
Improving the Behavior of the Nearest Neighbor Classifier against Noisy Data with Feature Weighting Schemes.
HAIS
José A. Sáez, Joaquín Derrac, Julián Luengo, Francisco Herrera
2014 C conf
Managing Borderline and Noisy Examples in Imbalanced Classification by Combining SMOTE with Ensemble Filtering.
IDEAL
José A. Sáez, Julián Luengo, Jerzy Stefanowski, Francisco Herrera
2014 J jnl
On the characterization of noise filters for self-training semi-supervised in nearest neighbor classification.
Neurocomputing
Isaac Triguero, José A. Sáez, Julián Luengo, Salvador García, Francisco Herrera
2014 J jnl
Statistical computation of feature weighting schemes through data estimation for nearest neighbor classifiers.
Pattern Recognit.
José A. Sáez, Joaquín Derrac, Julián Luengo, Francisco Herrera
2013 J jnl
A Survey of Discretization Techniques: Taxonomy and Empirical Analysis in Supervised Learning.
IEEE Trans. Knowl. Data Eng.
Salvador García, Julián Luengo, José Antonio Sáez, Victoria López, Francisco Herrera
2013 Misc conf
An Experimental Case of Study on the Behavior of Multiple Classifier Systems with Class Noise Datasets.
HAIS
José A. Sáez, Mikel Galar, Julián Luengo, Francisco Herrera
2013 J jnl
Predicting noise filtering efficacy with data complexity measures for nearest neighbor classification.
Pattern Recognit.
José A. Sáez, Julián Luengo, Francisco Herrera
2013 J jnl
Tackling the problem of classification with noisy data using Multiple Classifier Systems: Analysis of the performance and robustness.
Inf. Sci.
José A. Sáez, Mikel Galar, Julián Luengo, Francisco Herrera
2012 — conf
A First Study on Decomposition Strategies with Data with Class Noise Using Decision Trees.
HAIS (2)
José A. Sáez, Mikel Galar, Julián Luengo, Francisco Herrera
2012 — conf
A Preliminary Study on Selecting the Optimal Cut Points in Discretization by Evolutionary Algorithms.
ICPRAM (1)
Salvador García, Victoria López, Julián Luengo, Cristóbal J. Carmona, Francisco Herrera
2012 B conf
A preliminary study on missing data imputation in evolutionary fuzzy systems of subgroup discovery.
FUZZ-IEEE
Cristóbal J. Carmona, Julián Luengo, Pedro González, María José del Jesus
2012 J jnl
An analysis on the use of pre-processing methods in evolutionary fuzzy systems for subgroup discovery.
Expert Syst. Appl.
Cristóbal J. Carmona, Julián Luengo, Pedro González, María José del Jesus
2012 J jnl
Missing data imputation for fuzzy rule-based classification systems.
Soft Comput.
Julián Luengo, José A. Sáez, Francisco Herrera
2012 J jnl
On the choice of the best imputation methods for missing values considering three groups of classification methods.
Knowl. Inf. Syst.
Julián Luengo, Salvador García, Francisco Herrera
2012 J jnl
Shared domains of competence of approximate learning models using measures of separability of classes.
Inf. Sci.
Julián Luengo, Francisco Herrera
2011 J jnl
Addressing data complexity for imbalanced data sets: analysis of SMOTE-based oversampling and evolutionary undersampling.
Soft Comput.
Julián Luengo, Alberto Fernández, Salvador García, Francisco Herrera
2011 J jnl
Evolutionary selection of hyperrectangles in nested generalized exemplar learning.
Appl. Soft Comput.
Salvador García, Joaquín Derrac, Julián Luengo, Cristóbal J. Carmona, Francisco Herrera
2011 C conf
Fuzzy Rule Based Classification Systems versus crisp robust learners trained in presence of class noise's effects: A case of study.
ISDA
José A. Sáez, Julián Luengo, Francisco Herrera
2011 J jnl
KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework.
J. Multiple Valued Log. Soft Comput.
Jesús Alcalá-Fdez, Alberto Fernández, Julián Luengo, Joaquín Derrac, Salvador García
2010 Misc conf
A first study on the noise impact in classes for Fuzzy Rule Based Classification Systems.
ISKE
José A. Sáez, Julián Luengo, Francisco Herrera
2010 J jnl
A study on the use of imputation methods for experimentation with Radial Basis Function Network classifiers handling missing attribute values: The good synergy between RBFNs and EventCovering method.
Neural Networks
Julián Luengo, Salvador García, Francisco Herrera
2010 J jnl
Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power.
Inf. Sci.
Salvador García, Alberto Fernández, Julián Luengo, Francisco Herrera
2010 B conf
An extraction method for the characterization of the Fuzzy Rule Based Classification Systems' behavior using data complexity measures: A case of study with FH-GBML.
FUZZ-IEEE
Julián Luengo, Francisco Herrera
2010 J jnl
Domains of competence of fuzzy rule based classification systems with data complexity measures: A case of study using a fuzzy hybrid genetic based machine learning method.
Fuzzy Sets Syst.
Julián Luengo, Francisco Herrera
2010 J jnl
Genetics-Based Machine Learning for Rule Induction: State of the Art, Taxonomy, and Comparative Study.
IEEE Trans. Evol. Comput.
Alberto Fernández, Salvador García, Julián Luengo, Ester Bernadó-Mansilla, Francisco Herrera
2009 C conf
A First Approach to Nearest Hyperrectangle Selection by Evolutionary Algorithms.
ISDA
Salvador García, Joaquín Derrac, Julián Luengo, Francisco Herrera
2009 J jnl
A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability.
Soft Comput.
Salvador García, Alberto Fernández, Julián Luengo, Francisco Herrera
2009 J jnl
A study on the use of statistical tests for experimentation with neural networks: Analysis of parametric test conditions and non-parametric tests.
Expert Syst. Appl.
Julián Luengo, Salvador García, Francisco Herrera
2009 C conf
Addressing Data-Complexity for Imbalanced Data-Sets: A Preliminary Study on the Use of Preprocessing for C4.5.
ISDA
Julián Luengo, Alberto Fernández, Salvador García, Francisco Herrera
2009 — conf
Domains of Competence of Artificial Neural Networks Using Measures of Separability of Classes.
IWANN (1)
Julián Luengo, Francisco Herrera
2009 C conf
Implementation and Integration of Algorithms into the KEEL Data-Mining Software Tool.
IDEAL
Alberto Fernández, Julián Luengo, Joaquín Derrac, Jesús Alcalá-Fdez, Francisco Herrera
2009 — conf
On the use of Measures of Separability of Classes to Characterise the Domains of Competence of a Fuzzy Rule Based Classification System.
IFSA/EUSFLAT Conf.
Julián Luengo, Francisco Herrera
2007 Misc conf
A Study on the Use of Statistical Tests for Experimentation with Neural Networks.
IWANN
Julián Luengo, Salvador García, Francisco Herrera