Miguel A. Molina-Cabello

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 68

Top Topics

Background Modeling

Top Venues

Integr. Comput. Aided Eng.

Publications

Jose L. Ruiz-Casado, Miguel A. Molina-Cabello, Rafael M. Luque-Baena
Enhancing Histopathological Image Classification Performance through Synthetic Data Generation with Generative Adversarial Networks. Sensors 24 (12) (2024)
Ariadna Jiménez-Partinen, Miguel A. Molina-Cabello, Karl Thurnhofer-Hemsi, Esteban J. Palomo, Jorge Rodríguez-Capitán, Ana I. Molina-Ramos, Manuel Jiménez-Navarro
CADICA: a new dataset for coronary artery disease detection by using invasive coronary angiography. CoRR (2024)
José David Fernández-Rodríguez, Pablo Carmona-Martínez, Rafaela Benítez-Rochel, Miguel A. Molina-Cabello, Ezequiel López-Rubio
Unsupervised Detection of Incoming and Outgoing Traffic Flows in Video Sequences. IWINAC (2) (2024)
José A. Rodríguez-Rodríguez, Ezequiel López-Rubio, Juan A. Ángel-Ruiz, Miguel A. Molina-Cabello
The Impact of Noise and Brightness on Object Detection Methods. Sensors 24 (3) (2024)
Jose David Fernández Rodriguez, Jorge García-González, Rafaela Benítez-Rochel, Miguel A. Molina-Cabello, Gonzalo Ramos-Jiménez, Ezequiel López-Rubio
Automated detection of vehicles with anomalous trajectories in traffic surveillance videos. Integr. Comput. Aided Eng. 30 (3) (2023)
Ricardo Javier Fuentes-Fino, Saúl Calderón Ramírez, Enrique Domínguez, Ezequiel López-Rubio, David A. Elizondo, Miguel A. Molina-Cabello
An uncertainty estimator method based on the application of feature density to classify mammograms for breast cancer detection. Neural Comput. Appl. 35 (30) (2023)
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
Dataset Similarity to Assess Semisupervised Learning Under Distribution Mismatch Between the Labeled and Unlabeled Datasets. IEEE Trans. Artif. Intell. 4 (2) (2023)
Miguel A. Molina-Cabello, Karl Thurnhofer-Hemsi, David Molina-Cabello, Esteban J. Palomo
Are learning styles useful? A new software to analyze correlations with grades and a case study in engineering. Comput. Appl. Eng. Educ. 31 (3) (2023)
José M. Pérez-Bravo, José A. Rodríguez-Rodríguez, Jorge García-González, Miguel A. Molina-Cabello, Karl Thurnhofer-Hemsi, Ezequiel López-Rubio
Encoding Generative Adversarial Networks for Defense Against Image Classification Attacks. IWINAC (1) (2022)
Ricardo Javier Fuentes-Fino, Saúl Calderón Ramírez, Enrique Domínguez, Ezequiel López-Rubio, Marco A. Hernandez-Vasquez, Miguel A. Molina-Cabello
Feature Density as an Uncertainty Estimator Method in the Binary Classification Mammography Images Task for a Supervised Deep Learning Model. IWBBIO (2) (2022)
Saúl Calderón Ramírez, Diego Murillo-Hernandez, Kevin Rojas-Salazar, David A. Elizondo, Shengxiang Yang, Armaghan Moemeni, Miguel A. Molina-Cabello
A real use case of semi-supervised learning for mammogram classification in a local clinic of Costa Rica. Medical Biol. Eng. Comput. 60 (4) (2022)
Jose D. Fernández, Jorge García-González, Rafaela Benítez-Rochel, Miguel A. Molina-Cabello, Ezequiel López-Rubio
Anomalous Trajectory Detection for Automated Traffic Video Surveillance. IWINAC (1) (2022)
Willard Zamora-Cárdenas, Mauro Mendez, Saúl Calderón Ramírez, Martin Vargas, Gerardo Monge, Steve Quiros, David A. Elizondo, Miguel A. Molina-Cabello
Enforcing Morphological Information in Fully Convolutional Networks to Improve Cell Instance Segmentation in Fluorescence Microscopy Images. CoRR (2021)
Safa Hamreras, Bachir Boucheham, Miguel A. Molina-Cabello, Rafaela Benítez-Rochel, Ezequiel López-Rubio
Dynamic selection of classifiers for Content Based Image Retrieval. IJCNN (2021)
Miguel A. Molina-Cabello, José A. Rodríguez-Rodríguez, Karl Thurnhofer-Hemsi, Ezequiel López-Rubio
Histopathological image analysis for breast cancer diagnosis by ensembles of convolutional neural networks and genetic algorithms. IJCNN (2021)
Saúl Calderón Ramírez, Shengxiang Yang, Armaghan Moemeni, David A. Elizondo, Simon Colreavy-Donnelly, Luis Fernando Chavarria-Estrada, Miguel A. Molina-Cabello
Correcting data imbalance for semi-supervised COVID-19 detection using X-ray chest images. Appl. Soft Comput. 111 (2021)
Karl Thurnhofer-Hemsi, Miguel A. Molina-Cabello, Esteban J. Palomo, Ezequiel López-Rubio, Enrique Domínguez
Peer Assessments in Engineering: A Pilot Project. CISIS-ICEUTE (2021)
Saúl Calderón Ramírez, Diego Murillo-Hernandez, Kevin Rojas-Salazar, David A. Elizondo, Shengxiang Yang, Miguel A. Molina-Cabello
A Real Use Case of Semi-Supervised Learning for Mammogram Classification in a Local Clinic of Costa Rica. CoRR (2021)
José Miguel López-Rubio, Miguel A. Molina-Cabello, Gonzalo Ramos-Jiménez, Ezequiel López-Rubio
Classification of Images as Photographs or Paintings by Using Convolutional Neural Networks. IWANN (1) (2021)
Miguel A. Molina-Cabello, Karl Thurnhofer-Hemsi, Enrique Domínguez, Ezequiel López-Rubio, Esteban J. Palomo
Longitudinal Study of the Learning Styles Evolution in Engineering Degrees. CISIS-ICEUTE (2021)
Noel Khan, David A. Elizondo, Lipika Deka, Miguel A. Molina-Cabello
Fuzzy Logic Applied to System Monitors. IEEE Access 9 (2021)
José A. Rodríguez-Rodríguez, Miguel A. Molina-Cabello, Rafaela Benítez-Rochel, Ezequiel López-Rubio
Test time augmentation by regular shifting for deep denoising autoencoder networks. IJCNN (2021)
Jorge García-González, Miguel A. Molina-Cabello, Rafael M. Luque-Baena, Juan Miguel Ortiz-de-Lazcano-Lobato, Ezequiel López-Rubio
Road pollution estimation from vehicle tracking in surveillance videos by deep convolutional neural networks. Appl. Soft Comput. 113 (Part) (2021)
Karl Thurnhofer-Hemsi, Rosa Maza-Quiroga, Enrique Domínguez, Miguel A. Molina-Cabello, Ezequiel López-Rubio
Enhanced transfer learning model by image shifting on a square lattice for skin lesion malignancy assessment. IJCNN (2021)
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
Improving Uncertainty Estimation With Semi-Supervised Deep Learning for COVID-19 Detection Using Chest X-Ray Images. IEEE Access 9 (2021)
Saúl Calderón Ramírez, Diego Murillo-Hernandez, Kevin Rojas-Salazar, Luis-Alexander Calvo-Valverd, Shengxiang Yang, Armaghan Moemeni, David A. Elizondo, Ezequiel López-Rubio, Miguel A. Molina-Cabello
Improving Uncertainty Estimations for Mammogram Classification using Semi-Supervised Learning. IJCNN (2021)
Willard Zamora-Cárdenas, Mauro Mendez, Saúl Calderón Ramírez, Martin Vargas, Gerardo Monge, Steve Quiros, David A. Elizondo, Jordina Torrents-Barrena, Miguel A. Molina-Cabello
Enforcing Morphological Information in Fully Convolutional Networks to Improve Cell Instance Segmentation in Fluorescence Microscopy Images. IWANN (1) (2021)
Ezequiel López-Rubio, Miguel A. Molina-Cabello, Francisco M. Castro, Rafael M. Luque-Baena, Manuel J. Marín-Jiménez, Nicolás Guil
Anomalous object detection by active search with PTZ cameras. Expert Syst. Appl. 181 (2021)
Safa Hamreras, Bachir Boucheham, Miguel A. Molina-Cabello, Rafaela Benítez-Rochel, Ezequiel López-Rubio
Content based image retrieval by ensembles of deep learning object classifiers. Integr. Comput. Aided Eng. 27 (3) (2020)
José A. Rodríguez-Rodríguez, Miguel A. Molina-Cabello, Rafaela Benítez-Rochel, Ezequiel López-Rubio
The Effect of Noise and Brightness on Convolutional Deep Neural Networks. ICPR Workshops (6) (2020)
José A. Rodríguez-Rodríguez, Miguel A. Molina-Cabello, Rafaela Benítez-Rochel, Ezequiel López-Rubio
The Impact of Linear Motion Blur on the Object Recognition Efficiency of Deep Convolutional Neural Networks. ICPR Workshops (6) (2020)
Saúl Calderón Ramírez, Luis Oala, Jordina Torrents-Barrena, Shengxiang Yang, Armaghan Moemeni, Wojciech Samek, Miguel A. Molina-Cabello
MixMOOD: A systematic approach to class distribution mismatch in semi-supervised learning using deep dataset dissimilarity measures. CoRR (2020)
Miguel A. Molina-Cabello, Jorge García-González, Rafael M. Luque-Baena, Ezequiel López-Rubio
The effect of downsampling-upsampling strategy on foreground detection algorithms. Artif. Intell. Rev. 53 (7) (2020)
Karl Thurnhofer-Hemsi, Guillermo Ruiz-Álvarez, Rafael Marcos Luque Baena, Miguel A. Molina-Cabello, Ezequiel López-Rubio
Performance of Deep Learning and Traditional Techniques in Single Image Super-Resolution of Noisy Images. ICPR Workshops (6) (2020)
Karl Thurnhofer-Hemsi, Ezequiel López-Rubio, Núria Roé-Vellvé, Miguel A. Molina-Cabello
Multiobjective optimization of deep neural networks with combinations of Lp-norm cost functions for 3D medical image super-resolution. Integr. Comput. Aided Eng. 27 (3) (2020)
Saúl Calderón Ramírez, Shengxiang Yang, Armaghan Moemeni, David A. Elizondo, Simon Colreavy-Donnelly, Luis Fernando Chavarria-Estrada, Miguel A. Molina-Cabello
Correcting Data Imbalance for Semi-Supervised Covid-19 Detection Using X-ray Chest Images. CoRR (2020)
Miguel A. Molina-Cabello, David A. Elizondo, Rafael Marcos Luque Baena, Ezequiel López-Rubio
Aggregation of Convolutional Neural Network Estimations of Homographies by Color Transformations of the Inputs. IEEE Access 8 (2020)
Jorge García-González, Miguel A. Molina-Cabello, Rafael M. Luque-Baena, Juan Miguel Ortiz-de-Lazcano-Lobato, Ezequiel López-Rubio
Deep Autoencoder Architectures For Foreground Object Detection In Video Sequences Based On Probabilistic Mixture Models. ICIP (2020)
Saúl Calderón Ramírez, Raghvendra Giri, Shengxiang Yang, Armaghan Moemeni, Mario Umaña, David A. Elizondo, Jordina Torrents-Barrena, Miguel A. Molina-Cabello
Dealing with Scarce Labelled Data: Semi-supervised Deep Learning with Mix Match for Covid-19 Detection Using Chest X-ray Images. ICPR (2020)
José A. Rodríguez-Rodríguez, Miguel A. Molina-Cabello, Rafaela Benítez-Rochel, Ezequiel López-Rubio
The effect of image enhancement algorithms on convolutional neural networks. ICPR (2020)
Karl Thurnhofer-Hemsi, Ezequiel López-Rubio, Miguel A. Molina-Cabello, Kayvan Najarian
Radial basis function kernel optimization for Support Vector Machine classifiers. CoRR (2020)
Miguel A. Molina-Cabello, David A. Elizondo, Rafael M. Luque-Baena, Ezequiel López-Rubio
Foreground detection by ensembles of random polygonal tilings. Expert Syst. Appl. 161 (2020)
Miguel A. Molina-Cabello, Jorge García-González, Rafael Marcos Luque Baena, Karl Thurnhofer-Hemsi, Ezequiel López-Rubio
Adaptive estimation of optimal color transformations for deep convolutional network based homography estimation. ICPR (2020)
Karl Thurnhofer-Hemsi, Ezequiel López-Rubio, Núria Roé-Vellvé, Miguel A. Molina-Cabello
Deep Learning Networks with p-norm Loss Layers for Spatial Resolution Enhancement of 3D Medical Images. IWINAC (2) (2019)
Enrique Domínguez, Ezequiel López-Rubio, Miguel A. Molina-Cabello
Cooperative Evaluation Using Moodle. CISIS-ICEUTE (2019)
Jorge García-González, Juan Miguel Ortiz-de-Lazcano-Lobato, Rafael M. Luque-Baena, Miguel A. Molina-Cabello, Ezequiel López-Rubio
Foreground detection by probabilistic modeling of the features discovered by stacked denoising autoencoders in noisy video sequences. Pattern Recognit. Lett. 125 (2019)
Miguel A. Molina-Cabello, Cristian Accino, Ezequiel López-Rubio, Karl Thurnhofer-Hemsi
Optimization of Convolutional Neural Network Ensemble Classifiers by Genetic Algorithms. IWANN (2) (2019)
Safa Hamreras, Rafaela Benítez-Rochel, Bachir Boucheham, Miguel A. Molina-Cabello, Ezequiel López-Rubio
Content Based Image Retrieval by Convolutional Neural Networks. IWINAC (2) (2019)
Miguel A. Molina-Cabello, Benjamin N. Passow, Enrique Domínguez, David A. Elizondo, Jolanta Obszynska
Infering Air Quality from Traffic Data Using Transferable Neural Network Models. IWANN (1) (2019)
Esteban J. Palomo, Miguel A. Molina-Cabello, Ezequiel López-Rubio, Rafael Marcos Luque Baena
A New Self-Organizing Neural Gas Model based on Bregman Divergences. IJCNN (2018)
Karl Thurnhofer-Hemsi, Ezequiel López-Rubio, Núria Roé-Vellvé, Enrique Domínguez, Miguel A. Molina-Cabello
Super-resolution of 3D Magnetic Resonance Images by Random Shifting and Convolutional Neural Networks. IJCNN (2018)
Miguel A. Molina-Cabello, Ezequiel López-Rubio, Rafael M. Luque-Baena, María Jesús Rodríguez-Espinosa, Karl Thurnhofer-Hemsi
Blood Cell Classification Using the Hough Transform and Convolutional Neural Networks. WorldCIST (2) (2018)
Karl Thurnhofer-Hemsi, Ezequiel López-Rubio, Enrique Domínguez, Rafael Marcos Luque Baena, Miguel A. Molina-Cabello
Panorama construction for PTZ camera surveillance with the neural gas network. Expert Syst. J. Knowl. Eng. 35 (2) (2018)
Jorge García-González, Juan Miguel Ortiz-de-Lazcano-Lobato, Rafael M. Luque-Baena, Miguel A. Molina-Cabello, Ezequiel López-Rubio
Background Modeling for Video Sequences by Stacked Denoising Autoencoders. CAEPIA (2018)
Ezequiel López-Rubio, Miguel A. Molina-Cabello, Rafael Marcos Luque Baena, Enrique Domínguez
Foreground Detection by Competitive Learning for Varying Input Distributions. Int. J. Neural Syst. 28 (5) (2018)
Rafael Marcos Luque Baena, Miguel A. Molina-Cabello, Ezequiel López-Rubio, Enrique Domínguez
Foreground Detection Enhancement Using Pearson Correlation Filtering. IPMU (3) (2018)
Miguel A. Molina-Cabello, Ezequiel López-Rubio, Rafael M. Luque-Baena, Enrique Domínguez, Esteban J. Palomo
Foreground object detection for video surveillance by fuzzy logic based estimation of pixel illumination states. Log. J. IGPL 26 (6) (2018)
Miguel A. Molina-Cabello, Rafael Marcos Luque Baena, Ezequiel López-Rubio, Lipika Deka, Karl Thurnhofer-Hemsi
Road Pollution Estimation Using Static Cameras And Neural Networks. IJCNN (2018)
Francisco Javier López-Rubio, Ezequiel López-Rubio, Miguel A. Molina-Cabello, Rafael Marcos Luque Baena, Esteban J. Palomo, Enrique Domínguez
The effect of noise on foreground detection algorithms. Artif. Intell. Rev. 49 (3) (2018)
Miguel A. Molina-Cabello, Rafael Marcos Luque Baena, Ezequiel López-Rubio, Karl Thurnhofer-Hemsi
Vehicle type detection by ensembles of convolutional neural networks operating on super resolved images. Integr. Comput. Aided Eng. 25 (4) (2018)
Miguel A. Molina-Cabello, Rafael M. Luque-Baena, Ezequiel López-Rubio, Juan Miguel Ortiz-de-Lazcano-Lobato, Enrique Domínguez
A Growing Neural Gas Approach to Classify Vehicles in Traffic Environments. Int. J. Comput. Vis. Image Process. 7 (3) (2017)
Miguel A. Molina-Cabello, Rafael Marcos Luque Baena, Ezequiel López-Rubio, Karl Thurnhofer-Hemsi
Vehicle Type Detection by Convolutional Neural Networks. IWINAC (2) (2017)
Karl Thurnhofer-Hemsi, Ezequiel López-Rubio, Enrique Domínguez, Rafael Marcos Luque Baena, Miguel A. Molina-Cabello
Panoramic background modeling for PTZ cameras with competitive learning neural networks. IJCNN (2017)
Miguel A. Molina-Cabello, Ezequiel López-Rubio, Rafael Marcos Luque Baena, Enrique Domínguez, Karl Thurnhofer-Hemsi
Neural controller for PTZ cameras based on nonpanoramic foreground detection. IJCNN (2017)
Miguel A. Molina-Cabello, Rafael Marcos Luque Baena, Ezequiel López-Rubio, Juan Miguel Ortiz-de-Lazcano-Lobato, Enrique Domínguez, José Muñoz-Pérez
Vehicle Classification in Traffic Environments Using the Growing Neural Gas. IWANN (2) (2017)
Francisco Ortega-Zamorano, Miguel A. Molina-Cabello, Ezequiel López-Rubio, Esteban J. Palomo
Smart motion detection sensor based on video processing using self-organizing maps. Expert Syst. Appl. 64 (2016)
Miguel A. Molina-Cabello, Ezequiel López-Rubio, Rafael Marcos Luque Baena, Enrique Domínguez, Esteban J. Palomo
Pixel Features for Self-organizing Map Based Detection of Foreground Objects in Dynamic Environments. SOCO-CISIS-ICEUTE (2016)
Miguel A. Molina-Cabello, Ezequiel López-Rubio, Rafael Marcos Luque Baena, Esteban J. Palomo, Enrique Domínguez
Frame Size Reduction for Foreground Detection in Video Sequences. CAEPIA (2016)