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Julián Luengo

Julián Luengo

D-Index & Metrics

Computer Science

D-Index
33
Citations
13949
World Ranking
12348
National Ranking
226

Overview

Julián Luengo is affiliated with the University of Granada in Spain and has a research focus primarily in Computer Science, with 68 publications in this main field. Their work spans several subfields, including Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Computer Networks and Communications, and Industrial and Manufacturing Engineering.

Their research covers a range of topics, notably:

  • Anomaly Detection Techniques and Applications
  • Time Series Analysis and Forecasting
  • Network Security and Intrusion Detection
  • Machine Learning and Data Classification
  • Advanced Clustering Algorithms Research
  • Explainable Artificial Intelligence (XAI)
  • Advanced Neural Network Applications

Julián Luengo has contributed to several recent publications including:

  • "A tutorial on the segmentation of metallographic images: Taxonomy, new MetalDAM dataset, deep learning-based ensemble model, experimental analysis and challenges" (2021) in Information Fusion
  • "COVIDGR Dataset and COVID-SDNet Methodology for Predicting COVID-19 Based on Chest X-Ray Images" (2020) in IEEE Journal of Biomedical and Health Informatics (authored by Siham Tabik, a frequently collaborating researcher)

The publications occur frequently in several venues such as:

  • arXiv (Cornell University) with 8 publications
  • Neurocomputing with 4 publications
  • Information Sciences with 3 publications
  • Information Fusion with 2 publications
  • Applied Soft Computing with 2 publications

Collaboration is an important aspect of Julián Luengo's work, with frequent coauthors including Francisco Herrera, Ignacio Aguilera-Martos, Iván Sevillano-García, José-Ramón Cano, and Salvador García.

The scientist's output in anomaly detection, machine learning, and artificial intelligence is supported by work in time series and clustering methodologies. Their involvement with both theoretical and applied research is reflected through contributions to datasets, new methodologies, and frameworks for evaluation, indicating a breadth of focus within their area of expertise.

Best Publications

  • KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework

    J. Alcalá-Fdez;A. Fernández;J. Luengo;J. Derrac

  • Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power

    Salvador García;Alberto Fernández;Julián Luengo;Francisco Herrera

  • Data Preprocessing in Data Mining

    Salvador Garca;Julin Luengo;Francisco Herrera

  • A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability

    S. García;A. Fernández;J. Luengo;F. Herrera

  • Big data preprocessing: methods and prospects

    Salvador García;Sergio Ramírez-Gallego;Julián Luengo;José Manuel Benítez

  • SMOTE-IPF

    José A. Sáez;Julián Luengo;Jerzy Stefanowski;Francisco Herrera

  • A Survey of Discretization Techniques: Taxonomy and Empirical Analysis in Supervised Learning

    Salvador Garcia;J. Luengo;José Antonio Sáez;Victoria López

  • COVIDGR Dataset and COVID-SDNet Methodology for Predicting COVID-19 Based on Chest X-Ray Images

    S. Tabik;A. Gomez-Rios;J. L. Martin-Rodriguez;I. Sevillano-Garcia

  • Tutorial on practical tips of the most influential data preprocessing algorithms in data mining

    Salvador García;Salvador García;Julián Luengo;Francisco Herrera;Francisco Herrera

  • On the choice of the best imputation methods for missing values considering three groups of classification methods

    Julián Luengo;Salvador García;Francisco Herrera

  • KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining

    Isaac Triguero;Sergio González;Jose M. Moyano;Salvador García

  • Addressing data complexity for imbalanced data sets: analysis of SMOTE-based oversampling and evolutionary undersampling

    Julián Luengo;Alberto Fernández;Salvador García;Francisco Herrera

  • Genetics-Based Machine Learning for Rule Induction: State of the Art, Taxonomy, and Comparative Study

    A Fernández;S García;J Luengo;E Bernadó-Mansilla

  • Transforming big data into smart data: An insight on the use of the k-nearest neighbors algorithm to obtain quality data

    Isaac Triguero;Diego García-Gil;Jesús Maillo;Julián Luengo

  • A study on the use of statistical tests for experimentation with neural networks

    Julián Luengo;Salvador García;Francisco Herrera

  • Analyzing the presence of noise in multi-class problems: alleviating its influence with the One-vs-One decomposition

    José A. Sáez;Mikel Galar;Julián Luengo;Francisco Herrera

  • Enabling Smart Data: Noise filtering in Big Data classification

    Diego García-Gil;Julián Luengo;Salvador García;Francisco Herrera;Francisco Herrera

  • Towards highly accurate coral texture images classification using deep convolutional neural networks and data augmentation

    Anabel Gómez-Ríos;Siham Tabik;Julián Luengo;A. S. M. Shihavuddin

  • Tackling the problem of classification with noisy data using Multiple Classifier Systems: Analysis of the performance and robustness

    José A. SáEz;Mikel Galar;JuliáN Luengo;Francisco Herrera

  • 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

    Julián Luengo;Salvador García;Francisco Herrera

  • Predicting noise filtering efficacy with data complexity measures for nearest neighbor classification

    José A. SáEz;JuliáN Luengo;Francisco Herrera

  • On the characterization of noise filters for self-training semi-supervised in nearest neighbor classification

    Isaac Triguero;José A. Sáez;Julián Luengo;Salvador García

Frequent Co-Authors

Francisco Herrera
Francisco Herrera University of Granada
Salvador García
Salvador García University of Granada
Alberto Fernández
Alberto Fernández University of Granada
Isaac Triguero
Isaac Triguero University of Nottingham
Mikel Galar
Mikel Galar Universidad Publica De Navarra
André C. P. L. F. de Carvalho
André C. P. L. F. de Carvalho Universidade de São Paulo
Bartosz Krawczyk
Bartosz Krawczyk Rochester Institute of Technology
María José del Jesus
María José del Jesus University of Jaén
Jerzy Stefanowski
Jerzy Stefanowski Poznań University of Technology
José Manuel Benítez
José Manuel Benítez University of Granada

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