Publicaciones (184) Publicaciones de MARÍA JOSÉ DEL JESÚS DÍAZ

2023

  1. A distributed evolutionary fuzzy system-based method for the fusion of descriptive emerging patterns in data streams

    Information Fusion, Vol. 91, pp. 412-423

  2. Analysis of Transformer Model Applications

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

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

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

  4. XAIRE: An ensemble-based methodology for determining the relative importance of variables in regression tasks. Application to a hospital emergency department

    Artificial Intelligence in Medicine, Vol. 137

  5. mldr.resampling: Efficient reference implementations of multilabel resampling algorithms

    Neurocomputing, Vol. 559

2022

  1. Analysis of clustering methods for crop type mapping using satellite imagery

    Neurocomputing, Vol. 492, pp. 91-106

  2. Una visión actual de la inteligencia artificial: Recorrido histórico, datos y aprendizaje, confiabilidad y datos

    El derecho y la inteligencia artificial (Editorial Universidad de Granada), pp. 51-80

2021

  1. A Preliminary Many Objective Approach for Extracting Fuzzy Emerging Patterns

    Advances in Intelligent Systems and Computing

  2. A Preliminary Many Objective Approach for Extracting Fuzzy Emerging Patterns

    15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020): Burgos, Spain ; September 2020

  3. A Preliminary Study on Crop Classification with Unsupervised Algorithms for Time Series on Images with Olive Trees and Cereal Crops

    Advances in Intelligent Systems and Computing

  4. A Preliminary Study on Crop Classification with Unsupervised Algorithms for Time Series on Images with Olive Trees and Cereal Crops

    15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020): Burgos, Spain ; September 2020

  5. A cellular-based evolutionary approach for the extraction of emerging patterns in massive data streams

    Expert Systems with Applications, Vol. 183

  6. ClEnDAE: A classifier based on ensembles with built-in dimensionality reduction through denoising autoencoders

    Information Sciences, Vol. 565, pp. 146-176

  7. Implementation of Data Stream Classification Neural Network Models Over Big Data Platforms

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

2020

  1. An analysis of technological frameworks for data streams

    Progress in Artificial Intelligence, Vol. 9, Núm. 3, pp. 239-261

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

    Neurocomputing, Vol. 404, pp. 93-107

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

    Information Fusion, Vol. 54, pp. 44-60

  4. EvoAAA: An evolutionary methodology for automated neural autoencoder architecture search

    Integrated Computer-Aided Engineering

  5. FEPDS: A Proposal for the Extraction of Fuzzy Emerging Patterns in Data Streams

    IEEE Transactions on Fuzzy Systems, Vol. 28, Núm. 12, pp. 3193-3203

2019

  1. A Big Data Approach for the Extraction of Fuzzy Emerging Patterns

    Cognitive Computation, Vol. 11, Núm. 3, pp. 400-417