Miguel A. Molina-Cabello

73 papers B 14Journal 34Unranked 25
YearRankTypeTitle / Venue / Authors
2026 J jnl
Adaptive image enhancement for robust CNN classification under low illumination.
Expert Syst. Appl.
José A. Rodríguez-Rodríguez, Ezequiel López-Rubio, Salvador Jiménez-Segura, Miguel A. Molina-Cabello
2025 J jnl
Consensus-Based 3D View Generation from Noisy Images.
Int. J. Neural Syst.
José A. Rodríguez-Rodríguez, Miguel A. Molina-Cabello, Rafaela Benítez-Rochel, Ezequiel López-Rubio
2024 J jnl
CADICA: A new dataset for coronary artery disease detection by using invasive coronary angiography.
Expert Syst. J. Knowl. Eng.
Ariadna Jiménez-Partinen, Miguel A. Molina-Cabello, Karl Thurnhofer-Hemsi, Esteban J. Palomo, Jorge Rodríguez-Capitán, Ana I. Molina-Ramos, Manuel Jiménez-Navarro
2024 J jnl
CADICA: a new dataset for coronary artery disease detection by using invasive coronary angiography.
CoRR
Ariadna Jiménez-Partinen, Miguel A. Molina-Cabello, Karl Thurnhofer-Hemsi, Esteban J. Palomo, Jorge Rodríguez-Capitán, Ana I. Molina-Ramos, Manuel Jiménez-Navarro
2024 — conf
Early Breast Cancer Detection by Automated Analysis of Mammograms with Deep Convolutional Networks.
SOCO (2)
Guillermo Tell-González, Ezequiel López-Rubio, Rafaela Benítez-Rochel, Miguel A. Molina-Cabello
2024 — conf
Enhancing Echocardiography Quality with Diffusion Neural Models.
IWBBIO (2)
Antonio Fernández-Rodríguez, Ezequiel López-Rubio, Pablo Torres-Salomón, Jorge Rodríguez-Capitán, Manuel Jiménez-Navarro, Miguel A. Molina-Cabello
2024 J jnl
Enhancing Histopathological Image Classification Performance through Synthetic Data Generation with Generative Adversarial Networks.
Sensors
Jose L. Ruiz-Casado, Miguel A. Molina-Cabello, Rafael M. Luque-Baena
2024 J jnl
The Impact of Noise and Brightness on Object Detection Methods.
Sensors
José A. Rodríguez-Rodríguez, Ezequiel López-Rubio, Juan A. Ángel-Ruiz, Miguel A. Molina-Cabello
2024 — conf
Unsupervised Detection of Incoming and Outgoing Traffic Flows in Video Sequences.
IWINAC (2)
José David Fernández-Rodríguez, Pablo Carmona-Martínez, Rafaela Benítez-Rochel, Miguel A. Molina-Cabello, Ezequiel López-Rubio
2023 J jnl
An uncertainty estimator method based on the application of feature density to classify mammograms for breast cancer detection.
Neural Comput. Appl.
Ricardo Javier Fuentes-Fino, Saúl Calderón Ramírez, Enrique Domínguez, Ezequiel López-Rubio, David A. Elizondo, Miguel A. Molina-Cabello
2023 J jnl
Are learning styles useful? A new software to analyze correlations with grades and a case study in engineering.
Comput. Appl. Eng. Educ.
Miguel A. Molina-Cabello, Karl Thurnhofer-Hemsi, David Molina-Cabello, Esteban J. Palomo
2023 J jnl
Automated detection of vehicles with anomalous trajectories in traffic surveillance videos.
Integr. Comput. Aided Eng.
Jose David Fernández Rodriguez, Jorge García-González, Rafaela Benítez-Rochel, Miguel A. Molina-Cabello, Gonzalo Ramos-Jiménez, Ezequiel López-Rubio
2023 J jnl
Dataset Similarity to Assess Semisupervised Learning Under Distribution Mismatch Between the Labeled and Unlabeled Datasets.
IEEE Trans. Artif. Intell.
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
2022 J jnl
A real use case of semi-supervised learning for mammogram classification in a local clinic of Costa Rica.
Medical Biol. Eng. Comput.
Saúl Calderón Ramírez, Diego Murillo-Hernandez, Kevin Rojas-Salazar, David A. Elizondo, Shengxiang Yang, Armaghan Moemeni, Miguel A. Molina-Cabello
2022 — conf
Anomalous Trajectory Detection for Automated Traffic Video Surveillance.
IWINAC (1)
Jose D. Fernández, Jorge García-González, Rafaela Benítez-Rochel, Miguel A. Molina-Cabello, Ezequiel López-Rubio
2022 — conf
Encoding Generative Adversarial Networks for Defense Against Image Classification Attacks.
IWINAC (1)
José M. Pérez-Bravo, José A. Rodríguez-Rodríguez, Jorge García-González, Miguel A. Molina-Cabello, Karl Thurnhofer-Hemsi, Ezequiel López-Rubio
2022 — conf
Feature Density as an Uncertainty Estimator Method in the Binary Classification Mammography Images Task for a Supervised Deep Learning Model.
IWBBIO (2)
Ricardo Javier Fuentes-Fino, Saúl Calderón Ramírez, Enrique Domínguez, Ezequiel López-Rubio, Marco A. Hernandez-Vasquez, Miguel A. Molina-Cabello
2021 J jnl
A Real Use Case of Semi-Supervised Learning for Mammogram Classification in a Local Clinic of Costa Rica.
CoRR
Saúl Calderón Ramírez, Diego Murillo-Hernandez, Kevin Rojas-Salazar, David A. Elizondo, Shengxiang Yang, Miguel A. Molina-Cabello
2021 J jnl
Anomalous object detection by active search with PTZ cameras.
Expert Syst. Appl.
Ezequiel López-Rubio, Miguel A. Molina-Cabello, Francisco M. Castro, Rafael M. Luque-Baena, Manuel J. Marín-Jiménez, Nicolás Guil
2021 — conf
Classification of Images as Photographs or Paintings by Using Convolutional Neural Networks.
IWANN (1)
José Miguel López-Rubio, Miguel A. Molina-Cabello, Gonzalo Ramos-Jiménez, Ezequiel López-Rubio
2021 J jnl
Correcting data imbalance for semi-supervised COVID-19 detection using X-ray chest images.
Appl. Soft Comput.
Saúl Calderón Ramírez, Shengxiang Yang, Armaghan Moemeni, David A. Elizondo, Simon Colreavy-Donnelly, Luis Fernando Chavarria-Estrada, Miguel A. Molina-Cabello
2021 B conf
Dynamic selection of classifiers for Content Based Image Retrieval.
IJCNN
Safa Hamreras, Bachir Boucheham, Miguel A. Molina-Cabello, Rafaela Benítez-Rochel, Ezequiel López-Rubio
2021 — conf
Enforcing Morphological Information in Fully Convolutional Networks to Improve Cell Instance Segmentation in Fluorescence Microscopy Images.
IWANN (1)
Willard Zamora-Cárdenas, Mauro Mendez, Saúl Calderón Ramírez, Martin Vargas, Gerardo Monge, Steve Quirós, David A. Elizondo, Jordina Torrents-Barrena, Miguel A. Molina-Cabello
2021 J jnl
Enforcing Morphological Information in Fully Convolutional Networks to Improve Cell Instance Segmentation in Fluorescence Microscopy Images.
CoRR
Willard Zamora-Cárdenas, Mauro Mendez, Saúl Calderón Ramírez, Martin Vargas, Gerardo Monge, Steve Quirós, David A. Elizondo, Miguel A. Molina-Cabello
2021 B conf
Enhanced transfer learning model by image shifting on a square lattice for skin lesion malignancy assessment.
IJCNN
Karl Thurnhofer-Hemsi, Rosa Maza-Quiroga, Enrique Domínguez, Miguel A. Molina-Cabello, Ezequiel López-Rubio
2021 J jnl
Fuzzy Logic Applied to System Monitors.
IEEE Access
Noel Khan, David A. Elizondo, Lipika Deka, Miguel A. Molina-Cabello
2021 B conf
Histopathological image analysis for breast cancer diagnosis by ensembles of convolutional neural networks and genetic algorithms.
IJCNN
Miguel A. Molina-Cabello, José A. Rodríguez-Rodríguez, Karl Thurnhofer-Hemsi, Ezequiel López-Rubio
2021 J jnl
Improving Uncertainty Estimation With Semi-Supervised Deep Learning for COVID-19 Detection Using Chest X-Ray Images.
IEEE Access
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
2021 B conf
Improving Uncertainty Estimations for Mammogram Classification using Semi-Supervised Learning.
IJCNN
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
2021 — conf
Longitudinal Study of the Learning Styles Evolution in Engineering Degrees.
CISIS-ICEUTE
Miguel A. Molina-Cabello, Karl Thurnhofer-Hemsi, Enrique Domínguez, Ezequiel López-Rubio, Esteban J. Palomo
2021 — conf
Peer Assessments in Engineering: A Pilot Project.
CISIS-ICEUTE
Karl Thurnhofer-Hemsi, Miguel A. Molina-Cabello, Esteban J. Palomo, Ezequiel López-Rubio, Enrique Domínguez
2021 J jnl
Road pollution estimation from vehicle tracking in surveillance videos by deep convolutional neural networks.
Appl. Soft Comput.
Jorge García-González, Miguel A. Molina-Cabello, Rafael M. Luque-Baena, Juan Miguel Ortiz-de-Lazcano-Lobato, Ezequiel López-Rubio
2021 B conf
Test time augmentation by regular shifting for deep denoising autoencoder networks.
IJCNN
José A. Rodríguez-Rodríguez, Miguel A. Molina-Cabello, Rafaela Benítez-Rochel, Ezequiel López-Rubio
2020 B conf
Adaptive estimation of optimal color transformations for deep convolutional network based homography estimation.
ICPR
Miguel A. Molina-Cabello, Jorge García-González, Rafael Marcos Luque Baena, Karl Thurnhofer-Hemsi, Ezequiel López-Rubio
2020 J jnl
Aggregation of Convolutional Neural Network Estimations of Homographies by Color Transformations of the Inputs.
IEEE Access
Miguel A. Molina-Cabello, David A. Elizondo, Rafael Marcos Luque Baena, Ezequiel López-Rubio
2020 J jnl
Content based image retrieval by ensembles of deep learning object classifiers.
Integr. Comput. Aided Eng.
Safa Hamreras, Bachir Boucheham, Miguel A. Molina-Cabello, Rafaela Benítez-Rochel, Ezequiel López-Rubio
2020 J jnl
Correcting Data Imbalance for Semi-Supervised Covid-19 Detection Using X-ray Chest Images.
CoRR
Saúl Calderón Ramírez, Shengxiang Yang, Armaghan Moemeni, David A. Elizondo, Simon Colreavy-Donnelly, Luis Fernando Chavarria-Estrada, Miguel A. Molina-Cabello
2020 B conf
Dealing with Scarce Labelled Data: Semi-supervised Deep Learning with Mix Match for Covid-19 Detection Using Chest X-ray Images.
ICPR
Saúl Calderón Ramírez, Raghvendra Giri, Shengxiang Yang, Armaghan Moemeni, Mario Umaña, David A. Elizondo, Jordina Torrents-Barrena, Miguel A. Molina-Cabello
2020 B conf
Deep Autoencoder Architectures For Foreground Object Detection In Video Sequences Based On Probabilistic Mixture Models.
ICIP
Jorge García-González, Miguel A. Molina-Cabello, Rafael M. Luque-Baena, Juan Miguel Ortiz-de-Lazcano-Lobato, Ezequiel López-Rubio
2020 J jnl
Foreground detection by ensembles of random polygonal tilings.
Expert Syst. Appl.
Miguel A. Molina-Cabello, David A. Elizondo, Rafael M. Luque-Baena, Ezequiel López-Rubio
2020 J jnl
MixMOOD: A systematic approach to class distribution mismatch in semi-supervised learning using deep dataset dissimilarity measures.
CoRR
Saúl Calderón Ramírez, Luis Oala, Jordina Torrents-Barrena, Shengxiang Yang, Armaghan Moemeni, Wojciech Samek, Miguel A. Molina-Cabello
2020 J jnl
Multiobjective optimization of deep neural networks with combinations of Lp-norm cost functions for 3D medical image super-resolution.
Integr. Comput. Aided Eng.
Karl Thurnhofer-Hemsi, Ezequiel López-Rubio, Núria Roé-Vellvé, Miguel A. Molina-Cabello
2020 — conf
Performance of Deep Learning and Traditional Techniques in Single Image Super-Resolution of Noisy Images.
ICPR Workshops (6)
Karl Thurnhofer-Hemsi, Guillermo Ruiz-Álvarez, Rafael Marcos Luque Baena, Miguel A. Molina-Cabello, Ezequiel López-Rubio
2020 J jnl
Radial basis function kernel optimization for Support Vector Machine classifiers.
CoRR
Karl Thurnhofer-Hemsi, Ezequiel López-Rubio, Miguel A. Molina-Cabello, Kayvan Najarian
2020 — conf
The Effect of Noise and Brightness on Convolutional Deep Neural Networks.
ICPR Workshops (6)
José A. Rodríguez-Rodríguez, Miguel A. Molina-Cabello, Rafaela Benítez-Rochel, Ezequiel López-Rubio
2020 — conf
The Impact of Linear Motion Blur on the Object Recognition Efficiency of Deep Convolutional Neural Networks.
ICPR Workshops (6)
José A. Rodríguez-Rodríguez, Miguel A. Molina-Cabello, Rafaela Benítez-Rochel, Ezequiel López-Rubio
2020 J jnl
The effect of downsampling-upsampling strategy on foreground detection algorithms.
Artif. Intell. Rev.
Miguel A. Molina-Cabello, Jorge García-González, Rafael M. Luque-Baena, Ezequiel López-Rubio
2020 B conf
The effect of image enhancement algorithms on convolutional neural networks.
ICPR
José A. Rodríguez-Rodríguez, Miguel A. Molina-Cabello, Rafaela Benítez-Rochel, Ezequiel López-Rubio
2019 — conf
Content Based Image Retrieval by Convolutional Neural Networks.
IWINAC (2)
Safa Hamreras, Rafaela Benítez-Rochel, Bachir Boucheham, Miguel A. Molina-Cabello, Ezequiel López-Rubio
2019 — conf
Cooperative Evaluation Using Moodle.
CISIS-ICEUTE
Enrique Domínguez, Ezequiel López-Rubio, Miguel A. Molina-Cabello
2019 — conf
Deep Learning Networks with p-norm Loss Layers for Spatial Resolution Enhancement of 3D Medical Images.
IWINAC (2)
Karl Thurnhofer-Hemsi, Ezequiel López-Rubio, Núria Roé-Vellvé, Miguel A. Molina-Cabello
2019 J jnl
Foreground detection by probabilistic modeling of the features discovered by stacked denoising autoencoders in noisy video sequences.
Pattern Recognit. Lett.
Jorge García-González, Juan Miguel Ortiz-de-Lazcano-Lobato, Rafael M. Luque-Baena, Miguel A. Molina-Cabello, Ezequiel López-Rubio
2019 — conf
Infering Air Quality from Traffic Data Using Transferable Neural Network Models.
IWANN (1)
Miguel A. Molina-Cabello, Benjamin N. Passow, Enrique Domínguez, David A. Elizondo, Jolanta Obszynska
2019 — conf
Optimization of Convolutional Neural Network Ensemble Classifiers by Genetic Algorithms.
IWANN (2)
Miguel A. Molina-Cabello, Cristian Accino, Ezequiel López-Rubio, Karl Thurnhofer-Hemsi
2018 B conf
A New Self-Organizing Neural Gas Model based on Bregman Divergences.
IJCNN
Esteban J. Palomo, Miguel A. Molina-Cabello, Ezequiel López-Rubio, Rafael Marcos Luque Baena
2018 — conf
Background Modeling for Video Sequences by Stacked Denoising Autoencoders.
CAEPIA
Jorge García-González, Juan Miguel Ortiz-de-Lazcano-Lobato, Rafael M. Luque-Baena, Miguel A. Molina-Cabello, Ezequiel López-Rubio
2018 — conf
Blood Cell Classification Using the Hough Transform and Convolutional Neural Networks.
WorldCIST (2)
Miguel A. Molina-Cabello, Ezequiel López-Rubio, Rafael M. Luque-Baena, María Jesús Rodríguez-Espinosa, Karl Thurnhofer-Hemsi
2018 — conf
Foreground Detection Enhancement Using Pearson Correlation Filtering.
IPMU (3)
Rafael Marcos Luque Baena, Miguel A. Molina-Cabello, Ezequiel López-Rubio, Enrique Domínguez
2018 J jnl
Foreground Detection by Competitive Learning for Varying Input Distributions.
Int. J. Neural Syst.
Ezequiel López-Rubio, Miguel A. Molina-Cabello, Rafael Marcos Luque Baena, Enrique Domínguez
2018 J jnl
Foreground object detection for video surveillance by fuzzy logic based estimation of pixel illumination states.
Log. J. IGPL
Miguel A. Molina-Cabello, Ezequiel López-Rubio, Rafael M. Luque-Baena, Enrique Domínguez, Esteban J. Palomo
2018 J jnl
Panorama construction for PTZ camera surveillance with the neural gas network.
Expert Syst. J. Knowl. Eng.
Karl Thurnhofer-Hemsi, Ezequiel López-Rubio, Enrique Domínguez, Rafael Marcos Luque Baena, Miguel A. Molina-Cabello
2018 B conf
Road Pollution Estimation Using Static Cameras And Neural Networks.
IJCNN
Miguel A. Molina-Cabello, Rafael Marcos Luque Baena, Ezequiel López-Rubio, Lipika Deka, Karl Thurnhofer-Hemsi
2018 B conf
Super-resolution of 3D Magnetic Resonance Images by Random Shifting and Convolutional Neural Networks.
IJCNN
Karl Thurnhofer-Hemsi, Ezequiel López-Rubio, Núria Roé-Vellvé, Enrique Domínguez, Miguel A. Molina-Cabello
2018 J jnl
The effect of noise on foreground detection algorithms.
Artif. Intell. Rev.
Francisco Javier López-Rubio, Ezequiel López-Rubio, Miguel A. Molina-Cabello, Rafael Marcos Luque Baena, Esteban J. Palomo, Enrique Domínguez
2018 J jnl
Vehicle type detection by ensembles of convolutional neural networks operating on super resolved images.
Integr. Comput. Aided Eng.
Miguel A. Molina-Cabello, Rafael Marcos Luque Baena, Ezequiel López-Rubio, Karl Thurnhofer-Hemsi
2017 J jnl
A Growing Neural Gas Approach to Classify Vehicles in Traffic Environments.
Int. J. Comput. Vis. Image Process.
Miguel A. Molina-Cabello, Rafael M. Luque-Baena, Ezequiel López-Rubio, Juan Miguel Ortiz-de-Lazcano-Lobato, Enrique Domínguez
2017 B conf
Neural controller for PTZ cameras based on nonpanoramic foreground detection.
IJCNN
Miguel A. Molina-Cabello, Ezequiel López-Rubio, Rafael Marcos Luque Baena, Enrique Domínguez, Karl Thurnhofer-Hemsi
2017 B conf
Panoramic background modeling for PTZ cameras with competitive learning neural networks.
IJCNN
Karl Thurnhofer-Hemsi, Ezequiel López-Rubio, Enrique Domínguez, Rafael Marcos Luque Baena, Miguel A. Molina-Cabello
2017 — conf
Vehicle Classification in Traffic Environments Using the Growing Neural Gas.
IWANN (2)
Miguel A. Molina-Cabello, Rafael Marcos Luque Baena, Ezequiel López-Rubio, Juan Miguel Ortiz-de-Lazcano-Lobato, Enrique Domínguez, José Muñoz-Pérez
2017 — conf
Vehicle Type Detection by Convolutional Neural Networks.
IWINAC (2)
Miguel A. Molina-Cabello, Rafael Marcos Luque Baena, Ezequiel López-Rubio, Karl Thurnhofer-Hemsi
2016 — conf
Frame Size Reduction for Foreground Detection in Video Sequences.
CAEPIA
Miguel A. Molina-Cabello, Ezequiel López-Rubio, Rafael Marcos Luque Baena, Esteban J. Palomo, Enrique Domínguez
2016 — conf
Pixel Features for Self-organizing Map Based Detection of Foreground Objects in Dynamic Environments.
SOCO-CISIS-ICEUTE
Miguel A. Molina-Cabello, Ezequiel López-Rubio, Rafael Marcos Luque Baena, Enrique Domínguez, Esteban J. Palomo
2016 J jnl
Smart motion detection sensor based on video processing using self-organizing maps.
Expert Syst. Appl.
Francisco Ortega-Zamorano, Miguel A. Molina-Cabello, Ezequiel López-Rubio, Esteban J. Palomo