World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
9247
World Ranking
11014
National Ranking
180

Overview

Mikel Galar is affiliated with Universidad Publica De Navarra in Spain and has contributed extensively to the fields of Computer Science and Engineering. Their research focuses primarily on Artificial Intelligence and Computer Vision and Pattern Recognition, with additional work addressing Media Technology, Experimental and Cognitive Psychology, and Management Science and Operations Research.

The primary areas of study for Mikel Galar include:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Media Technology
  • Experimental and Cognitive Psychology
  • Management Science and Operations Research

The scientist's research topics encompass:

  • Emotion and Mood Recognition
  • Face recognition and analysis
  • Multi-Criteria Decision Making
  • Advanced Image Fusion Techniques
  • Automated Road and Building Extraction
  • Remote-Sensing Image Classification
  • Imbalanced Data Classification Techniques

Mikel Galar has published 55 works in Computer Science and 23 in Engineering. They have contributed notably to venues such as arXiv (Cornell University), SSRN Electronic Journal, Fuzzy Sets and Systems, Remote Sensing, and Applied Soft Computing.

Frequent publication venues include:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Fuzzy Sets and Systems
  • Remote Sensing
  • Applied Soft Computing

The scientist's recent papers exemplify their research scope and include:

  • "d-Choquet integrals: Choquet integrals based on dissimilarities" (2020, Fuzzy Sets and Systems)
  • "Network traffic analysis through node behaviour classification: a graph-based approach with temporal dissection and data-level preprocessing" (2022, Computers & Security)
  • "Super-Resolution of Sentinel-2 Images Using Convolutional Neural Networks and Real Ground Truth Data" (2020, Remote Sensing)
  • "A Deep Learning Approach to an Enhanced Building Footprint and Road Detection in High-Resolution Satellite Imagery" (2021, Remote Sensing)
  • "EUSC: A clustering-based surrogate model to accelerate evolutionary undersampling in imbalanced classification" (2020, Applied Soft Computing)

Collaborations are a significant aspect of their work, with frequent co-authors including:

  • Daniel Paternain
  • Iris Dominguez-Catena
  • Isaac Triguero
  • Christian Ayala
  • C. Aranda

Mikel Galar has also contributed to book publications, including a title published by Cambridge University Press:

  • "Large-Scale Data Analytics with Python and Spark" (2023)

Best Publications

  • A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches

    M. Galar;A. Fernandez;E. Barrenechea;H. Bustince

  • An overview of ensemble methods for binary classifiers in multi-class problems: Experimental study on one-vs-one and one-vs-all schemes

    Mikel Galar;Alberto Fernández;Edurne Barrenechea;Humberto Bustince

  • EUSBoost: Enhancing ensembles for highly imbalanced data-sets by evolutionary undersampling

    Mikel Galar;Alberto Fernández;Edurne Barrenechea;Francisco Herrera

  • Analysing the classification of imbalanced data-sets with multiple classes: Binarization techniques and ad-hoc approaches

    Alberto FernáNdez;Victoria LóPez;Mikel Galar;MaríA José Del Jesus

  • Learning from Imbalanced Data Sets

    Alberto Ferna ndez;Salvador Garci a;Mikel Galar;Ronaldo C

  • Evolutionary undersampling boosting for imbalanced classification of breast cancer malignancy

    Bartosz Krawczyk;Mikel Galar;Łukasz Jeleń;Francisco Herrera

  • A New Approach to Interval-Valued Choquet Integrals and the Problem of Ordering in Interval-Valued Fuzzy Set Applications

    Humberto Bustince;Mikel Galar;Benjamin Bedregal;Anna Kolesarova

  • Medical diagnosis of cardiovascular diseases using an interval-valued fuzzy rule-based classification system

    José Antonio Sanz;Mikel Galar;Aranzazu Jurio;Antonio Brugos

  • 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

  • Enhancing Multiclass Classification in FARC-HD Fuzzy Classifier: On the Synergy Between $n$ -Dimensional Overlap Functions and Decomposition Strategies

    Mikel Elkano;Mikel Galar;Jose Antonio Sanz;Alberto Fernandez

  • A survey on fingerprint minutiae-based local matching for verification and identification

    Daniel Peralta;Mikel Galar;Isaac Triguero;Daniel Paternain

  • Fuzzy Rule-Based Classification Systems for multi-class problems using binary decomposition strategies

    Mikel Elkano;Mikel Galar;Jose Sanz;Humberto Bustince

  • 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

  • Dynamic classifier selection for One-vs-One strategy: Avoiding non-competent classifiers

    Mikel Galar;Alberto Fernández;Edurne Barrenechea;Humberto Bustince

  • DRCW-OVO

    Mikel Galar;Alberto Fernández;Edurne Barrenechea;Francisco Herrera

  • Consensus via penalty functions for decision making in ensembles in fuzzy rule-based classification systems

    Mikel Elkano;Mikel Galar;Jos Antonio Sanz;Paula Fernanda Schiavo

  • Ordering-based pruning for improving the performance of ensembles of classifiers in the framework of imbalanced datasets

    Mikel Galar;Alberto Fernández;Edurne Barrenechea;Humberto Bustince

  • Dynamic ensemble selection for multi-class classification with one-class classifiers

    Bartosz Krawczyk;Mikel Galar;Michał Woźniak;Humberto Bustince

  • INFFC: An iterative class noise filter based on the fusion of classifiers with noise sensitivity control

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

  • CHI-BD: A fuzzy rule-based classification system for Big Data classification problems

    Mikel Elkano;Mikel Galar;José Antonio Sanz;Humberto Bustince

Frequent Co-Authors

Humberto Bustince
Humberto Bustince Universidad Publica De Navarra
Francisco Herrera
Francisco Herrera University of Granada
Alberto Fernández
Alberto Fernández University of Granada
Edurne Barrenechea
Edurne Barrenechea Universidad Publica De Navarra
Bartosz Krawczyk
Bartosz Krawczyk Rochester Institute of Technology
Javier Fernández
Javier Fernández Universidad Publica De Navarra
Isaac Triguero
Isaac Triguero University of Nottingham
Miguel Pagola
Miguel Pagola Universidad Publica De Navarra
Salvador García
Salvador García University of Granada
Julián Luengo
Julián Luengo University of Granada

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