A Robust Two-Stage System for Image Segmentation. - Ezequiel López-Rubio; José Muñoz-Pérez; José Antonio Gómez-Ruiz (ICPR, 2000)

Expansive and Competitive Neural Networks. - José Antonio Gómez-Ruiz; José Muñoz-Pérez; Ezequiel López-Rubio; M. Angeles García-Bernal (IWANN (1), 2001)

Dynamic Topology Networks for Colour Image Compression. - Ezequiel López-Rubio; José Muñoz-Pérez; José Antonio Gómez-Ruiz (IWANN (2), 2001)

Invariant pattern identification by self-organising networks. - Ezequiel López-Rubio; José Muñoz-Pérez; José Antonio Gómez-Ruiz (Pattern Recognit. Lett., 2001)

Detección de esqueletos de caracteres mediante una red neuronal competitiva basada en segmentos. - José Antonio Gómez-Ruiz; José Muñoz-Pérez; M. Angeles García-Bernal; Ezequiel López-Rubio (Inteligencia Artif., 2002)

Self Organizing Dynamic Graphs. - Ezequiel López-Rubio; José Muñoz-Pérez; José Antonio Gómez-Ruiz (Neural Process. Lett., 2002)

Expansive and Competitive Learning for Vector Quantization. - José Muñoz-Pérez; José Antonio Gómez-Ruiz; Ezequiel López-Rubio; M. Angeles García-Bernal (Neural Process. Lett., 2002)

Principal Components Analysis Competitive Learning. - Ezequiel López-Rubio; José Muñoz-Pérez; José Antonio Gómez-Ruiz (IWANN (1), 2003)

A four-stage system for blind colour image segmentation. - Ezequiel López-Rubio; José Muñoz-Pérez; José Antonio Gómez-Ruiz (Integr. Comput. Aided Eng., 2003)

New learning rules for the ASSOM network. - Ezequiel López-Rubio; José Muñoz-Pérez; José Antonio Gómez-Ruiz; Enrique Domínguez Merino (Neural Comput. Appl., 2003)

Dynamic Selection of Model Parameters in Principal Components Analysis Neural Networks. - Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato; María del Carmen Vargas-González; José Miguel López-Rubio (ECAI, 2004)

Principal Components Analysis Competitive Learning. - Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato; José Muñoz-Pérez; José Antonio Gómez-Ruiz (Neural Comput., 2004)

A principal components analysis self-organizing map. - Ezequiel López-Rubio; José Muñoz-Pérez; José Antonio Gómez-Ruiz (Neural Networks, 2004)

Intrinsic Dimensionality Maps with the PCASOM. - Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato; María del Carmen Vargas-González; José Miguel López-Rubio (IWANN, 2005)

Global-local learning strategies in probabilistic principal components analysis. - Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato; Domingo López-Rodríguez; Enrique Mérida Casermeiro; María del Carmen Vargas-González (Artificial Intelligence and Soft Computing, 2006)

Image Compression by Vector Quantization with Recurrent Discrete Networks. - Domingo López-Rodríguez; Enrique Mérida Casermeiro; Juan Miguel Ortiz-de-Lazcano-Lobato; Ezequiel López-Rubio (ICANN (2), 2006)

Local Selection of Model Parameters in Probability Density Function Estimation. - Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato; Domingo López-Rodríguez; Enrique Mérida Casermeiro; María del Carmen Vargas-González (ICANN (2), 2006)

Spicules-based competitive neural network. - José Antonio Gómez-Ruiz; José Muñoz-Pérez; M. Angeles García-Bernal; Ezequiel López-Rubio (ESANN, 2007)

Soft Clustering for Nonparametric Probability Density Function Estimation. - Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato; Domingo López-Rodríguez; María del Carmen Vargas-González (ICANN (1), 2007)

Automatic Model Selection for Probabilistic PCA. - Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato; Domingo López-Rodríguez; María del Carmen Vargas-González (IWANN, 2007)

Self-organization of Probabilistic PCA Models. - Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato; Domingo López-Rodríguez; María del Carmen Vargas-González (IWANN, 2007)

Robust Nonparametric Probability Density Estimation by Soft Clustering. - Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato; Domingo López-Rodríguez; María del Carmen Vargas-González (ICANN (1), 2008)

Soft clustering for nonparametric probability density function estimation. - Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato (Pattern Recognit. Lett., 2008)

Object Tracking in Video Sequences by Unsupervised Learning. - Rafael Marcos Luque; Juan Miguel Ortiz-de-Lazcano-Lobato; Ezequiel López-Rubio; Esteban J. Palomo (CAIP, 2009)

Nonparametric Location Estimation for Probability Density Function Learning. - Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato; María del Carmen Vargas-González (IWANN (1), 2009)

Probabilistic Self-Organizing Graphs. - Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato; María del Carmen Vargas-González (IWANN (1), 2009)

Robust Location and Spread Measures for Nonparametric Probability Density Function Estimation. - Ezequiel López-Rubio (Int. J. Neural Syst., 2009)

Dynamic Competitive Probabilistic Principal Components Analysis. - Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato (Int. J. Neural Syst., 2009)

Multivariate Student-t self-organizing maps. - Ezequiel López-Rubio (Neural Networks, 2009)

Automatic Model Selection by Cross-Validation for Probabilistic PCA. - Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato (Neural Process. Lett., 2009)

Probabilistic PCA Self-Organizing Maps. - Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato; Domingo López-Rodríguez (IEEE Trans. Neural Networks, 2009)

Probabilistic self-organizing maps for qualitative data. - Ezequiel López-Rubio (Neural Networks, 2010)

Restoration of images corrupted by Gaussian and uniform impulsive noise. - Ezequiel López-Rubio (Pattern Recognit., 2010)

Probabilistic self-organizing maps for continuous data. - Ezequiel López-Rubio (IEEE Trans. Neural Networks, 2010)

GA-based feature selection approach in biometric hand systems. - Rafael Marcos Luque; David A. Elizondo; Ezequiel López-Rubio; Esteban J. Palomo (IJCNN, 2011)

Reduction of JPEG Compression Artifacts by Kernel Regression and Probabilistic Self-Organizing Maps. - María Nieves Florentín-Núñez; Ezequiel López-Rubio; Francisco Javier López-Rubio (IWANN (2), 2011)

Feature Weighting in Competitive Learning for Multiple Object Tracking in Video Sequences. - Rafael Marcos Luque; Juan Miguel Ortiz-de-Lazcano-Lobato; Ezequiel López-Rubio; Enrique Domínguez; Esteban J. Palomo (IWANN (2), 2011)

Stochastic approximation for background modelling. - Ezequiel López-Rubio; Rafael Marcos Luque Baena (Comput. Vis. Image Underst., 2011)

Foreground Detection in Video Sequences with Probabilistic Self-Organizing Maps. - Ezequiel López-Rubio; Rafael Marcos Luque Baena; Enrique Domínguez (Int. J. Neural Syst., 2011)

Stochastic approximation learning for mixtures of multivariate elliptical distributions. - Ezequiel López-Rubio (Neurocomputing, 2011)

Dynamic topology learning with the probabilistic self-organizing graph. - Ezequiel López-Rubio; Esteban José Palomo-Ferrer; Juan Miguel Ortiz-de-Lazcano-Lobato; María del Carmen Vargas-González (Neurocomputing, 2011)

Kernel regression based feature extraction for 3D MR image denoising. - Ezequiel López-Rubio; María Nieves Florentín-Núñez (Medical Image Anal., 2011)

Growing Hierarchical Probabilistic Self-Organizing Graphs. - Ezequiel López-Rubio; Esteban J. Palomo (IEEE Trans. Neural Networks, 2011)

Feature Selection of Hand Biometrical Traits Based on Computational Intelligence Techniques. - Rafael Marcos Luque; David A. Elizondo; Ezequiel López-Rubio; Esteban J. Palomo (Computational Intelligence for Privacy and Security, 2012)

A Self-organizing Map for Traffic Flow Monitoring. - Rafael Marcos Luque Baena; Ezequiel López-Rubio; Enrique Domínguez; Esteban José Palomo; José Manuel Jerez (IWANN (2), 2013)

Hierarchical Self-Organizing Networks for Multispectral Data Visualization. - Esteban José Palomo; Ezequiel López-Rubio; Enrique Domínguez; Rafael Marcos Luque Baena (IWANN (2), 2013)

Assessment of geometric features for individual identification and verification in biometric hand systems. - Rafael M. Luque-Baena; David A. Elizondo; Ezequiel López-Rubio; Esteban J. Palomo; Tim Watson (Expert Syst. Appl., 2013)

Adaptive kernel regression and probabilistic self-organizing maps for JPEG image deblocking. - María Nieves Florentín-Núñez; Ezequiel López-Rubio; Francisco Javier López-Rubio (Neurocomputing, 2013)

A Competitive Neural Network for Multiple Object Tracking in Video Sequence Analysis. - Rafael Marcos Luque Baena; Juan Miguel Ortiz-de-Lazcano-Lobato; Ezequiel López-Rubio; Enrique Domínguez; Esteban J. Palomo (Neural Process. Lett., 2013)

Improving the Quality of Self-Organizing Maps by Self-Intersection Avoidance. - Ezequiel López-Rubio (IEEE Trans. Neural Networks Learn. Syst., 2013)

Color space selection for self-organizing map based foreground detection in video sequences. - Francisco Javier López-Rubio; Ezequiel López-Rubio; Rafael Marcos Luque Baena; Enrique Domínguez; Esteban J. Palomo (IJCNN, 2014)

Bregman Divergences for Growing Hierarchical Self-Organizing Networks. - Ezequiel López-Rubio; Esteban José Palomo; Enrique Domínguez (Int. J. Neural Syst., 2014)

Grid topologies for the self-organizing map. - Ezequiel López-Rubio; Antonio Díaz Ramos (Neural Networks, 2014)

A Histogram Transform for ProbabilityDensity Function Estimation. - Ezequiel López-Rubio (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

An adaptive system for compressed video deblocking. - Ezequiel López-Rubio; Rafael Marcos Luque Baena (Signal Process., 2014)

Visualization of Complex Datasets with the Self-Organizing Spanning Tree. - Ezequiel López-Rubio; Esteban José Palomo; Rafael Marcos Luque Baena; Enrique Domínguez (IWANN (1), 2015)

Computational Intelligence Techniques in Medicine. - Ezequiel López-Rubio; David A. Elizondo; Martin Grootveld; José M. Jerez; Rafael M. Luque-Baena (Comput. Math. Methods Medicine, 2015)

Features for stochastic approximation based foreground detection. - Francisco Javier López-Rubio; Ezequiel López-Rubio (Comput. Vis. Image Underst., 2015)

Robust self-organization with M-estimators. - Ezequiel López-Rubio; Esteban J. Palomo; Enrique Domínguez (Neurocomputing, 2015)

Probability density function estimation with the frequency polygon transform. - Ezequiel López-Rubio; José Muñoz-Pérez (Inf. Sci., 2015)

Local color transformation analysis for sudden illumination change detection. - Francisco Javier López-Rubio; Ezequiel López-Rubio (Image Vis. Comput., 2015)

Foreground detection for moving cameras with stochastic approximation. - Francisco Javier López-Rubio; Ezequiel López-Rubio (Pattern Recognit. Lett., 2015)

A self-organizing map to improve vehicle detection in flow monitoring systems. - Rafael Marcos Luque Baena; Ezequiel López-Rubio; Enrique Domínguez; Esteban J. Palomo; José M. Jerez (Soft Comput., 2015)

Frame Size Reduction for Foreground Detection in Video Sequences. - Miguel A. Molina-Cabello; Ezequiel López-Rubio; Rafael Marcos Luque Baena; Esteban J. Palomo; Enrique Domínguez (CAEPIA, 2016)

Extended abstract: A color quantization approach based on the Growing Neural Forest. - Esteban J. Palomo; Ezequiel López-Rubio (LA-CCI, 2016)

Pixel Features for Self-organizing Map Based Detection of Foreground Objects in Dynamic Environments. - Miguel A. Molina-Cabello; Ezequiel López-Rubio; Rafael Marcos Luque Baena; Enrique Domínguez; Esteban J. Palomo (SOCO-CISIS-ICEUTE, 2016)

Smart motion detection sensor based on video processing using self-organizing maps. - Francisco Ortega-Zamorano; Miguel A. Molina-Cabello; Ezequiel López-Rubio; Esteban J. Palomo (Expert Syst. Appl., 2016)

Learning Topologies with the Growing Neural Forest. - Esteban José Palomo; Ezequiel López-Rubio (Int. J. Neural Syst., 2016)

Selecting the Color Space for Self-Organizing Map Based Foreground Detection in Video. - Francisco Javier López-Rubio; Enrique Domínguez; Esteban J. Palomo; Ezequiel López-Rubio; Rafael Marcos Luque Baena (Neural Process. Lett., 2016)

Superresolution from a Single Noisy Image by the Median Filter Transform. - Ezequiel López-Rubio (SIAM J. Imaging Sci., 2016)

Neural controller for PTZ cameras based on nonpanoramic foreground detection. - Miguel A. Molina-Cabello; Ezequiel López-Rubio; Rafael Marcos Luque Baena; Enrique Domínguez; Karl Thurnhofer-Hemsi (IJCNN, 2017)

Panoramic background modeling for PTZ cameras with competitive learning neural networks. - Karl Thurnhofer-Hemsi; Ezequiel López-Rubio; Enrique Domínguez; Rafael Marcos Luque Baena; Miguel A. Molina-Cabello (IJCNN, 2017)

Vehicle Classification in Traffic Environments Using the Growing Neural Gas. - Miguel A. Molina-Cabello; Rafael Marcos Luque Baena; Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato; Enrique Domínguez; José Muñoz-Pérez (IWANN (2), 2017)

Unsupervised Color Quantization with the Growing Neural Forest. - Esteban José Palomo; Jesús Benito-Picazo; Ezequiel López-Rubio; Enrique Domínguez (IWANN (2), 2017)

Motion Detection by Microcontroller for Panning Cameras. - Jesús Benito-Picazo; Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato; Enrique Domínguez; Esteban J. Palomo (IWINAC (2), 2017)

Vehicle Type Detection by Convolutional Neural Networks. - Miguel A. Molina-Cabello; Rafael Marcos Luque Baena; Ezequiel López-Rubio; Karl Thurnhofer-Hemsi (IWINAC (2), 2017)

Developing Cooperative Evaluation Methodologies in Higher Education. - Enrique Domínguez; Ezequiel López-Rubio (SOCO-CISIS-ICEUTE, 2017)

Growing Neural Forest-Based Color Quantization Applied to RGB Images. - Jesús Benito-Picazo; Ezequiel López-Rubio; Enrique Domínguez (Int. J. Comput. Vis. Image Process., 2017)

A Growing Neural Gas Approach to Classify Vehicles in Traffic Environments. - Miguel A. Molina-Cabello; Rafael M. Luque-Baena; Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato; Enrique Domínguez (Int. J. Comput. Vis. Image Process., 2017)

Robust Fitting of Ellipsoids by Separating Interior and Exterior Points During Optimization. - Ezequiel López-Rubio; Karl Thurnhofer-Hemsi; Óscar David de Cózar-Macías; Elidia Beatriz Blázquez-Parra; José Muñoz-Pérez; I. Ladrón de Guevara-López (J. Math. Imaging Vis., 2017)

Dynamic tree topology learning by self-organization. - Ezequiel López-Rubio; Rafael M. Luque-Baena; Esteban J. Palomo; Enrique Domínguez (Neural Comput. Appl., 2017)

The Growing Hierarchical Neural Gas Self-Organizing Neural Network. - Esteban J. Palomo; Ezequiel López-Rubio (IEEE Trans. Neural Networks Learn. Syst., 2017)

Background Modeling for Video Sequences by Stacked Denoising Autoencoders. - Jorge García-González; Juan Miguel Ortiz-de-Lazcano-Lobato; Rafael M. Luque-Baena; Miguel A. Molina-Cabello; Ezequiel López-Rubio (CAEPIA, 2018)

Deep learning-based anomalous object detection system powered by microcontroller for PTZ cameras. - Jesús Benito-Picazo; Enrique Domínguez; Esteban J. Palomo; Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato (IJCNN, 2018)

Road Pollution Estimation Using Static Cameras And Neural Networks. - Miguel A. Molina-Cabello; Rafael Marcos Luque Baena; Ezequiel López-Rubio; Lipika Deka; Karl Thurnhofer-Hemsi (IJCNN, 2018)

A New Self-Organizing Neural Gas Model based on Bregman Divergences. - Esteban J. Palomo; Miguel A. Molina-Cabello; Ezequiel López-Rubio; Rafael Marcos Luque Baena (IJCNN, 2018)

Super-resolution of 3D Magnetic Resonance Images by Random Shifting and Convolutional Neural Networks. - Karl Thurnhofer-Hemsi; Ezequiel López-Rubio; Núria Roé-Vellvé; Enrique Domínguez; Miguel A. Molina-Cabello (IJCNN, 2018)

Foreground Detection Enhancement Using Pearson Correlation Filtering. - Rafael Marcos Luque Baena; Miguel A. Molina-Cabello; Ezequiel López-Rubio; Enrique Domínguez (IPMU (3), 2018)

Blood Cell Classification Using the Hough Transform and Convolutional Neural Networks. - Miguel A. Molina-Cabello; Ezequiel López-Rubio; Rafael M. Luque-Baena; María Jesús Rodríguez-Espinosa; Karl Thurnhofer-Hemsi (WorldCIST (2), 2018)

The effect of noise on foreground detection algorithms. - Francisco Javier López-Rubio; Ezequiel López-Rubio; Miguel A. Molina-Cabello; Rafael Marcos Luque Baena; Esteban J. Palomo; Enrique Domínguez (Artif. Intell. Rev., 2018)

Panorama construction for PTZ camera surveillance with the neural gas network. - Karl Thurnhofer-Hemsi; Ezequiel López-Rubio; Enrique Domínguez; Rafael Marcos Luque Baena; Miguel A. Molina-Cabello (Expert Syst. J. Knowl. Eng., 2018)

Vehicle type detection by ensembles of convolutional neural networks operating on super resolved images. - Miguel A. Molina-Cabello; Rafael Marcos Luque Baena; Ezequiel López-Rubio; Karl Thurnhofer-Hemsi (Integr. Comput. Aided Eng., 2018)

Foreground object detection for video surveillance by fuzzy logic based estimation of pixel illumination states. - Miguel A. Molina-Cabello; Ezequiel López-Rubio; Rafael M. Luque-Baena; Enrique Domínguez; Esteban J. Palomo (Log. J. IGPL, 2018)

Foreground Detection by Competitive Learning for Varying Input Distributions. - Ezequiel López-Rubio; Miguel A. Molina-Cabello; Rafael Marcos Luque Baena; Enrique Domínguez (Int. J. Neural Syst., 2018)

Unsupervised learning by cluster quality optimization. - Ezequiel López-Rubio; Esteban J. Palomo; Francisco Ortega-Zamorano (Inf. Sci., 2018)

Computational Functionalism for the Deep Learning Era. - Ezequiel López-Rubio (Minds Mach., 2018)

A fast robust geometric fitting method for parabolic curves. - Ezequiel López-Rubio; Karl Thurnhofer-Hemsi; Elidia Beatriz Blázquez-Parra; Óscar David de Cózar-Macías; M. Carmen Ladrón-de-Guevara-Muñoz (Pattern Recognit., 2018)

Cooperative Evaluation Using Moodle. - Enrique Domínguez; Ezequiel López-Rubio; Miguel A. Molina-Cabello (CISIS-ICEUTE, 2019)

Diabetic Wound Segmentation using Convolutional Neural Networks. - Can Cui; Karl Thurnhofer-Hemsi; Reza Soroushmehr; Abinash Mishra; Jonathan Gryak; Enrique Domínguez; Kayvan Najarian; Ezequiel López-Rubio (EMBC, 2019)

Optimization of Convolutional Neural Network Ensemble Classifiers by Genetic Algorithms. - Miguel A. Molina-Cabello; Cristian Accino; Ezequiel López-Rubio; Karl Thurnhofer-Hemsi (IWANN (2), 2019)

Deep Learning-Based Security System Powered by Low Cost Hardware and Panoramic Cameras. - Jesús Benito-Picazo; Enrique Domínguez; Esteban J. Palomo; Ezequiel López-Rubio (IWINAC (2), 2019)

Background Modeling by Shifted Tilings of Stacked Denoising Autoencoders. - Jorge García-González; Juan Miguel Ortiz-de-Lazcano-Lobato; Rafael M. Luque-Baena; Ezequiel López-Rubio (IWINAC (2), 2019)

Content Based Image Retrieval by Convolutional Neural Networks. - Safa Hamreras; Rafaela Benítez-Rochel; Bachir Boucheham; Miguel A. Molina-Cabello; Ezequiel López-Rubio (IWINAC (2), 2019)

Deep Learning Networks with p-norm Loss Layers for Spatial Resolution Enhancement of 3D Medical Images. - Karl Thurnhofer-Hemsi; Ezequiel López-Rubio; Núria Roé-Vellvé; Miguel A. Molina-Cabello (IWINAC (2), 2019)

Motion detection with low cost hardware for PTZ cameras. - Jesús Benito-Picazo; Enrique Domínguez; Esteban J. Palomo; Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato (Integr. Comput. Aided Eng., 2019)

Piecewise Polynomial Activation Functions for Feedforward Neural Networks. - Ezequiel López-Rubio; Francisco Ortega-Zamorano; Enrique Domínguez; José Muñoz-Pérez (Neural Process. Lett., 2019)

Foreground detection by probabilistic modeling of the features discovered by stacked denoising autoencoders in noisy video sequences. - Jorge García-González; Juan Miguel Ortiz-de-Lazcano-Lobato; Rafael M. Luque-Baena; Miguel A. Molina-Cabello; Ezequiel López-Rubio (Pattern Recognit. Lett., 2019)

Foreground Detection by Probabilistic Mixture Models Using Semantic Information from Deep Networks. - Jorge García-González; Juan Miguel Ortiz-de-Lazcano-Lobato; Rafael M. Luque-Baena; Ezequiel López-Rubio (ECAI, 2020)

Deep Autoencoder Architectures For Foreground Object Detection In Video Sequences Based On Probabilistic Mixture Models. - Jorge García-González; Miguel A. Molina-Cabello; Rafael M. Luque-Baena; Juan Miguel Ortiz-de-Lazcano-Lobato; Ezequiel López-Rubio (ICIP, 2020)

Super-Resolution of 3D MRI Corrupted by Heavy Noise With the Median Filter Transform. - Karl Thurnhofer-Hemsi; Ezequiel López-Rubio; Núria Roé-Vellvé; Lipika Deka (ICIP, 2020)

Adaptive estimation of optimal color transformations for deep convolutional network based homography estimation. - Miguel A. Molina-Cabello; Jorge García-González; Rafael Marcos Luque Baena; Karl Thurnhofer-Hemsi; Ezequiel López-Rubio (ICPR, 2020)

The Impact of Linear Motion Blur on the Object Recognition Efficiency of Deep Convolutional Neural Networks. - José A. Rodríguez-Rodríguez; Miguel A. Molina-Cabello; Rafaela Benítez-Rochel; Ezequiel López-Rubio (ICPR Workshops (6), 2020)

The Effect of Noise and Brightness on Convolutional Deep Neural Networks. - José A. Rodríguez-Rodríguez; Miguel A. Molina-Cabello; Rafaela Benítez-Rochel; Ezequiel López-Rubio (ICPR Workshops (6), 2020)

The effect of image enhancement algorithms on convolutional neural networks. - José A. Rodríguez-Rodríguez; Miguel A. Molina-Cabello; Rafaela Benítez-Rochel; Ezequiel López-Rubio (ICPR, 2020)

Performance of Deep Learning and Traditional Techniques in Single Image Super-Resolution of Noisy Images. - Karl Thurnhofer-Hemsi; Guillermo Ruiz-Álvarez; Rafael Marcos Luque Baena; Miguel A. Molina-Cabello; Ezequiel López-Rubio (ICPR Workshops (6), 2020)

Aggregation of Convolutional Neural Network Estimations of Homographies by Color Transformations of the Inputs. - Miguel A. Molina-Cabello; David A. Elizondo; Rafael Marcos Luque Baena; Ezequiel López-Rubio (IEEE Access, 2020)

The effect of downsampling-upsampling strategy on foreground detection algorithms. - Miguel A. Molina-Cabello; Jorge García-González; Rafael M. Luque-Baena; Ezequiel López-Rubio (Artif. Intell. Rev., 2020)

Radial basis function kernel optimization for Support Vector Machine classifiers. - Karl Thurnhofer-Hemsi; Ezequiel López-Rubio; Miguel A. Molina-Cabello; Kayvan Najarian (CoRR, 2020)

Foreground detection by ensembles of random polygonal tilings. - Miguel A. Molina-Cabello; David A. Elizondo; Rafael M. Luque-Baena; Ezequiel López-Rubio (Expert Syst. Appl., 2020)

Deep learning-based video surveillance system managed by low cost hardware and panoramic cameras. - Jesús Benito-Picazo; Enrique Domínguez; Esteban J. Palomo; Ezequiel López-Rubio (Integr. Comput. Aided Eng., 2020)

Background subtraction by probabilistic modeling of patch features learned by deep autoencoders. - Jorge García-González; Juan Miguel Ortiz-de-Lazcano-Lobato; Rafael M. Luque-Baena; Ezequiel López-Rubio (Integr. Comput. Aided Eng., 2020)

Content based image retrieval by ensembles of deep learning object classifiers. - Safa Hamreras; Bachir Boucheham; Miguel A. Molina-Cabello; Rafaela Benítez-Rochel; Ezequiel López-Rubio (Integr. Comput. Aided Eng., 2020)

Multiobjective optimization of deep neural networks with combinations of Lp-norm cost functions for 3D medical image super-resolution. - Karl Thurnhofer-Hemsi; Ezequiel López-Rubio; Núria Roé-Vellvé; Miguel A. Molina-Cabello (Integr. Comput. Aided Eng., 2020)

Deep learning-based super-resolution of 3D magnetic resonance images by regularly spaced shifting. - Karl Thurnhofer-Hemsi; Ezequiel López-Rubio; Enrique Domínguez; Rafael Marcos Luque Baena; Núria Roé-Vellvé (Neurocomputing, 2020)

Exploratory Data Analysis and Foreground Detection with the Growing Hierarchical Neural Forest. - Esteban J. Palomo; Ezequiel López-Rubio; Francisco Ortega-Zamorano; Rafaela Benítez-Rochel (Neural Process. Lett., 2020)

Ellipse fitting by spatial averaging of random ensembles. - Karl Thurnhofer-Hemsi; Ezequiel López-Rubio; Elidia Beatriz Blázquez-Parra; M. Carmen Ladrón-de-Guevara-Muñoz; Óscar David de Cózar-Macías (Pattern Recognit., 2020)

The Forbidden Region Self-Organizing Map Neural Network. - Antonio Díaz Ramos; Ezequiel López-Rubio; Esteban J. Palomo (IEEE Trans. Neural Networks Learn. Syst., 2020)

Longitudinal Study of the Learning Styles Evolution in Engineering Degrees. - Miguel A. Molina-Cabello; Karl Thurnhofer-Hemsi; Enrique Domínguez; Ezequiel López-Rubio; Esteban J. Palomo (CISIS-ICEUTE, 2021)

Peer Assessments in Engineering: A Pilot Project. - Karl Thurnhofer-Hemsi; Miguel A. Molina-Cabello; Esteban J. Palomo; Ezequiel López-Rubio; Enrique Domínguez (CISIS-ICEUTE, 2021)

Deep learning-based anomalous object detection system for panoramic cameras managed by a Jetson TX2 board. - Jesús Benito-Picazo; Enrique Domínguez; Esteban J. Palomo; Gonzalo Ramos-Jiménez; Ezequiel López-Rubio (IJCNN, 2021)

Dynamic selection of classifiers for Content Based Image Retrieval. - Safa Hamreras; Bachir Boucheham; Miguel A. Molina-Cabello; Rafaela Benítez-Rochel; Ezequiel López-Rubio (IJCNN, 2021)

Histopathological image analysis for breast cancer diagnosis by ensembles of convolutional neural networks and genetic algorithms. - Miguel A. Molina-Cabello; José A. Rodríguez-Rodríguez; Karl Thurnhofer-Hemsi; Ezequiel López-Rubio (IJCNN, 2021)

Improving Uncertainty Estimations for Mammogram Classification using Semi-Supervised Learning. - Saúl Calderón Ramírez; Diego Murillo-Hernandez; Kevin Rojas-Salazar; Luis-Alexander Calvo-Valverde; Shengxiang Yang; Armaghan Moemeni; David A. Elizondo; Ezequiel López-Rubio; Miguel A. Molina-Cabello (IJCNN, 2021)

Test time augmentation by regular shifting for deep denoising autoencoder networks. - José A. Rodríguez-Rodríguez; Miguel A. Molina-Cabello; Rafaela Benítez-Rochel; Ezequiel López-Rubio (IJCNN, 2021)

Enhanced transfer learning model by image shifting on a square lattice for skin lesion malignancy assessment. - Karl Thurnhofer-Hemsi; Rosa Maza-Quiroga; Enrique Domínguez; Miguel A. Molina-Cabello; Ezequiel López-Rubio (IJCNN, 2021)

Classification of Images as Photographs or Paintings by Using Convolutional Neural Networks. - José Miguel López-Rubio; Miguel A. Molina-Cabello; Gonzalo Ramos-Jiménez; Ezequiel López-Rubio (IWANN (1), 2021)

Rician Noise Estimation for 3D Magnetic Resonance Images Based on Benford's Law. - Rosa Maza-Quiroga; Karl Thurnhofer-Hemsi; Domingo López-Rodríguez; Ezequiel López-Rubio (MICCAI (6), 2021)

Foreground Segmentation Improvement by Image Denoising Preprocessing Applied to Noisy Video Sequences. - Jorge García-González; Juan Miguel Ortiz-de-Lazcano-Lobato; Rafael Marcos Luque Baena; Ezequiel López-Rubio (SOCO, 2021)

Hierarchical Color Quantization with a Neural Gas Model Based on Bregman Divergences. - Esteban J. Palomo; Jesús Benito-Picazo; Enrique Domínguez; Ezequiel López-Rubio; Francisco Ortega-Zamorano (SOCO, 2021)

Improving Uncertainty Estimation With Semi-Supervised Deep Learning for COVID-19 Detection Using Chest X-Ray Images. - Saúl Calderón Ramírez; Shengxiang Yang; Armaghan Moemeni; Simon Colreavy-Donnelly; David A. Elizondo; Luis Oala; Jorge Rodríguez-Capitán; Manuel Jiménez-Navarro; Ezequiel López-Rubio; Miguel A. Molina-Cabello (IEEE Access, 2021)

Skin Lesion Classification by Ensembles of Deep Convolutional Networks and Regularly Spaced Shifting. - Karl Thurnhofer-Hemsi; Ezequiel López-Rubio; Enrique Domínguez; David A. Elizondo (IEEE Access, 2021)

Road pollution estimation from vehicle tracking in surveillance videos by deep convolutional neural networks. - Jorge García-González; Miguel A. Molina-Cabello; Rafael M. Luque-Baena; Juan Miguel Ortiz-de-Lazcano-Lobato; Ezequiel López-Rubio (Appl. Soft Comput., 2021)

Improved detection of small objects in road network sequences. - Iván García; Rafael Marcos Luque; Ezequiel López-Rubio (CoRR, 2021)

Anomalous object detection by active search with PTZ cameras. - Ezequiel López-Rubio; Miguel A. Molina-Cabello; Francisco M. Castro; Rafael M. Luque-Baena; Manuel J. Marín-Jiménez; Nicolás Guil (Expert Syst. Appl., 2021)

Ensemble ellipse fitting by spatial median consensus. - Karl Thurnhofer-Hemsi; Ezequiel López-Rubio; Elidia Beatriz Blázquez-Parra; M. Carmen Ladrón-de-Guevara-Muñoz; Óscar David de Cózar-Macías (Inf. Sci., 2021)

Throwing light on black boxes: emergence of visual categories from deep learning. - Ezequiel López-Rubio (Synth., 2021)

Data science and molecular biology: prediction and mechanistic explanation. - Ezequiel López-Rubio; Emanuele Ratti (Synth., 2021)

Moving Object Detection in Noisy Video Sequences Using Deep Convolutional Disentangled Representations. - Jorge García-González; Rafael M. Luque-Baena; Juan Miguel Ortiz-de-Lazcano-Lobato; Ezequiel López-Rubio (ICIP, 2022)

Enhanced Perspective Generation by Consensus of NeX neural models. - Marcos Sergio Pacheco dos Santos Lima Junior; Jose David Fernández Rodriguez; Juan Miguel Ortiz-de-Lazcano-Lobato; Ezequiel López-Rubio; Enrique Domínguez (IJCNN, 2022)

Feature Density as an Uncertainty Estimator Method in the Binary Classification Mammography Images Task for a Supervised Deep Learning Model. - Ricardo Javier Fuentes-Fino; Saúl Calderón Ramírez; Enrique Domínguez; Ezequiel López-Rubio; Marco A. Hernandez-Vasquez; Miguel A. Molina-Cabello (IWBBIO (2), 2022)

Enhanced Image Segmentation by a Novel Test Time Augmentation and Super-Resolution. - Iván García Aguilar; Jorge García-González; Rafael Marcos Luque Baena; Ezequiel López-Rubio; Enrique Domínguez Merino (IWINAC (1), 2022)

Anomalous Trajectory Detection for Automated Traffic Video Surveillance. - Jose D. Fernández 001; Jorge García-González; Rafaela Benítez-Rochel; Miguel A. Molina-Cabello; Ezequiel López-Rubio (IWINAC (1), 2022)

Analysis of Functional Connectome Pipelines for the Diagnosis of Autism Spectrum Disorders. - Clara Jiménez-Valverde; Rosa Maza-Quiroga; Domingo López-Rodríguez; Karl Thurnhofer-Hemsi; Ezequiel López-Rubio; Rafael Marcos Luque Baena (IWINAC (1), 2022)

A Novel Continual Learning Approach for Competitive Neural Networks. - Esteban J. Palomo; Juan Miguel Ortiz-de-Lazcano-Lobato; José David Fernández-Rodríguez; Ezequiel López-Rubio; Rosa Maza-Quiroga (IWINAC (1), 2022)

Encoding Generative Adversarial Networks for Defense Against Image Classification Attacks. - José M. Pérez-Bravo; José A. Rodríguez-Rodríguez; Jorge García-González; Miguel A. Molina-Cabello; Karl Thurnhofer-Hemsi; Ezequiel López-Rubio (IWINAC (1), 2022)

Vehicle Overtaking Hazard Detection over Onboard Cameras Using Deep Convolutional Networks. - Jorge García-González; Iván García Aguilar; Daniel Medina; Rafael Marcos Luque Baena; Ezequiel López-Rubio; Enrique Domínguez (SOCO, 2022)

Improved detection of small objects in road network sequences using CNN and super resolution. - Iván García Aguilar; Rafael Marcos Luque Baena; Ezequiel López-Rubio (Expert Syst. J. Knowl. Eng., 2022)

Minimal Optimal Region Generation for Enhanced Object Detection in Aerial Images Using Super-Resolution and Convolutional Neural Networks. - Iván García Aguilar; Lipika Deka; Rafael Marcos Luque Baena; Enrique Domínguez; Ezequiel López-Rubio (IWANN (1), 2023)

Parallel Processing Applied to Object Detection with a Jetson TX2 Embedded System. - Jesús Benito-Picazo; Jose David Fernández Rodriguez; Enrique Domínguez; Esteban J. Palomo; Ezequiel López-Rubio (SOCO (2), 2023)

Optimized instance segmentation by super-resolution and maximal clique generation. - Iván García Aguilar; Jorge García-González; Rafael M. Luque-Baena; Ezequiel López-Rubio; Enrique Domínguez (Integr. Comput. Aided Eng., 2023)

Dynamic learning rates for continual unsupervised learning. - José David Fernández-Rodríguez; Esteban José Palomo; Juan Miguel Ortiz-de-Lazcano-Lobato; Gonzalo Ramos-Jiménez; Ezequiel López-Rubio (Integr. Comput. Aided Eng., 2023)

Automated detection of vehicles with anomalous trajectories in traffic surveillance videos. - Jose David Fernández Rodriguez; Jorge García-González; Rafaela Benítez-Rochel; Miguel A. Molina-Cabello; Gonzalo Ramos-Jiménez; Ezequiel López-Rubio (Integr. Comput. Aided Eng., 2023)

Automated labeling of training data for improved object detection in traffic videos by fine-tuned deep convolutional neural networks. - Iván García Aguilar; Jorge García-González; Rafael Marcos Luque Baena; Ezequiel López-Rubio (Pattern Recognit. Lett., 2023)

Dataset Similarity to Assess Semisupervised Learning Under Distribution Mismatch Between the Labeled and Unlabeled Datasets. - Saúl Calderón Ramírez; Luis Oala; Jordina Torrents-Barrena; Shengxiang Yang; David A. Elizondo; Armaghan Moemeni; Simon Colreavy-Donnelly; Wojciech Samek; Miguel A. Molina-Cabello; Ezequiel López-Rubio (IEEE Trans. Artif. Intell., 2023)

A convolutional autoencoder and a neural gas model based on Bregman divergences for hierarchical color quantization. - José David Fernández-Rodríguez; Esteban J. Palomo; Jesús Benito-Picazo; Enrique Domínguez; Ezequiel López-Rubio; Francisco Ortega-Zamorano (Neurocomputing, 2023)

Small-Scale Urban Object Anomaly Detection Using Convolutional Neural Networks with Probability Estimation. - Iván García Aguilar; Rafael Marcos Luque Baena; Enrique Domínguez; Ezequiel López-Rubio (Sensors, 2023)

Object detection in traffic videos: an optimized approach using super-resolution and maximal clique algorithm. - Iván García Aguilar; Jorge García-González; Rafael Marcos Luque Baena; Ezequiel López-Rubio (Neural Comput. Appl., 2023)

An uncertainty estimator method based on the application of feature density to classify mammograms for breast cancer detection. - Ricardo Javier Fuentes-Fino; Saúl Calderón Ramírez; Enrique Domínguez; Ezequiel López-Rubio; David A. Elizondo; Miguel A. Molina-Cabello (Neural Comput. Appl., 2023)

Regression of the Rician Noise Level in 3D Magnetic Resonance Images from the Distribution of the First Significant Digit. - Rosa Maza-Quiroga; Karl Thurnhofer-Hemsi; Domingo López-Rodríguez; Ezequiel López-Rubio (Axioms, 2023)

Enhancing Echocardiography Quality with Diffusion Neural Models. - Antonio Fernández-Rodríguez; Ezequiel López-Rubio; Pablo Torres-Salomón; Jorge Rodríguez-Capitán; Manuel Jiménez-Navarro; Miguel A. Molina-Cabello (IWBBIO (2), 2024)

Enhanced Cellular Detection Using Convolutional Neural Networks and Sliding Window Super-Resolution Inference. - Iván García Aguilar; Rostyslav Zavoiko; Jose David Fernández Rodriguez; Rafael Marcos Luque Baena; Ezequiel López-Rubio (IWINAC (2), 2024)

Unsupervised Detection of Incoming and Outgoing Traffic Flows in Video Sequences. - José David Fernández-Rodríguez; Pablo Carmona-Martínez; Rafaela Benítez-Rochel; Miguel A. Molina-Cabello; Ezequiel López-Rubio (IWINAC (2), 2024)

Automated Semantic Labelling of Images Generated with Deep Diffusion Probabilistic Models. - José David Fernández-Rodríguez; Jesús Benito-Picazo; Iván García Aguilar; Ezequiel López-Rubio (SOCO (1), 2024)

Novel Positional Encoding Methods for Neural Rendering. - Daniel Molina-Pinel; Jorge García-González; Enrique Domínguez; Ezequiel López-Rubio (SOCO (2), 2024)

Early Breast Cancer Detection by Automated Analysis of Mammograms with Deep Convolutional Networks. - Guillermo Tell-González; Ezequiel López-Rubio; Rafaela Benítez-Rochel; Miguel A. Molina-Cabello (SOCO (2), 2024)

Detection of dangerously approaching vehicles over onboard cameras by speed estimation from apparent size. - Iván García Aguilar; Jorge García-González; Daniel Medina; Rafael Marcos Luque Baena; Enrique Domínguez; Ezequiel López-Rubio (Neurocomputing, 2024)

The Impact of Noise and Brightness on Object Detection Methods. - José A. Rodríguez-Rodríguez; Ezequiel López-Rubio; Juan A. Ángel-Ruiz; Miguel A. Molina-Cabello (Sensors, 2024)

Semi-Supervised Semantic Image Segmentation by Deep Diffusion Models and Generative Adversarial Networks. - José Ángel Díaz-Francés; José David Fernández-Rodríguez; Karl Thurnhofer-Hemsi; Ezequiel López-Rubio (Int. J. Neural Syst., 2024)

Hyperparameter optimization of YOLO models for invasive coronary angiography lesion detection and assessment. - Mario Pascual-González; Ariadna Jiménez-Partinen; Esteban J. Palomo; Ezequiel López-Rubio; Almudena Ortega-Gómez (Comput. Biol. Medicine, 2025)

Learning to shape beams: Using a neural network to control a beamforming antenna. - José David Fernández-Rodríguez; Iván García Aguilar; Rafael Marcos Luque Baena; Ezequiel López-Rubio; Marcos Baena-Molina; Juan Francisco Valenzuela-Valdés (Comput. Networks, 2025)

Latent diffusion for arbitrary zoom MRI super-resolution. - Jorge Andrés Mármol-Rivera; José David Fernández-Rodríguez; Beatriz Asenjo; Ezequiel López-Rubio (Expert Syst. Appl., 2025)

Representation of Molecules by Sequences of Instructions. - Karl Thurnhofer-Hemsi; Iván García Aguilar; José David Fernández-Rodríguez; Ezequiel López-Rubio (J. Chem. Inf. Model., 2025)

Enhanced generation of automatically labelled image segmentation datasets by advanced style interpreter deep architectures. - Marcos Sergio Pacheco dos Santos Lima Junior; Ezequiel López-Rubio; Juan Miguel Ortiz-de-Lazcano-Lobato; José David Fernández-Rodríguez (Pattern Recognit. Lett., 2025)

Enhanced deep-style interpreter for automatic synthesis of annotated medical images. - Marcos Sergio Pacheco dos Santos Lima Junior; Juan Miguel Ortiz-de-Lazcano-Lobato; José David Fernández-Rodríguez; Ezequiel López-Rubio (Neural Comput. Appl., 2025)