Miguel A. Molina-Cabello
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
32
Venues
7
Active years
2017–2026
Best venue rank
B
Where they publish
Papers
32 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | IWINAC | Dealing with the Feature Distribution of Mammogram Images by Means of GAN Architectures When Using Multiple Datasets. | Ricardo Javier Fuentes-Fino, Miguel A. Molina-Cabello, Enrique Domnguez |
| 2026 | IWINAC | Impact of Preprocessing Algorithms on Deep Learning-Driven Stenosis Classification in Invasive Coronary Angiography. | Ariadna Jimnez-Partinen, Miguel A. Molina-Cabello, Juan Marques-Garrido, Mara Paulina Ordez-Walkowiak, Jorge Rodrguez-Capitn, Ana I. Molina-Ramos, Manuel Jimnez-Navarro |
| 2024 | IWINAC | Unsupervised Detection of Incoming and Outgoing Traffic Flows in Video Sequences. | Jos David Fernndez-Rodrguez, Pablo Carmona-Martnez, Rafaela Bentez-Rochel, Miguel A. Molina-Cabello, Ezequiel Lpez-Rubio |
| 2022 | IWINAC | Anomalous Trajectory Detection for Automated Traffic Video Surveillance. | Jose D. Fernndez, Jorge Garca-Gonzlez, Rafaela Bentez-Rochel, Miguel A. Molina-Cabello, Ezequiel Lpez-Rubio |
| 2022 | IWINAC | Encoding Generative Adversarial Networks for Defense Against Image Classification Attacks. | Jos M. Prez-Bravo, Jos A. Rodrguez-Rodrguez, Jorge Garca-Gonzlez, Miguel A. Molina-Cabello, Karl Thurnhofer-Hemsi, Ezequiel Lpez-Rubio |
| 2021 | IJCNN | Dynamic selection of classifiers for Content Based Image Retrieval. | Safa Hamreras, Bachir Boucheham, Miguel A. Molina-Cabello, Rafaela Bentez-Rochel, Ezequiel Lpez-Rubio |
| 2021 | IJCNN | Histopathological image analysis for breast cancer diagnosis by ensembles of convolutional neural networks and genetic algorithms. | Miguel A. Molina-Cabello, Jos A. Rodrguez-Rodrguez, Karl Thurnhofer-Hemsi, Ezequiel Lpez-Rubio |
| 2021 | IJCNN | Improving Uncertainty Estimations for Mammogram Classification using Semi-Supervised Learning. | Sal Caldern Ramrez, Diego Murillo-Hernandez, Kevin Rojas-Salazar, Luis-Alexander Calvo-Valverde, Shengxiang Yang, Armaghan Moemeni, David A. Elizondo, Ezequiel Lpez-Rubio, Miguel A. Molina-Cabello |
| 2021 | IJCNN | Test time augmentation by regular shifting for deep denoising autoencoder networks. | Jos A. Rodrguez-Rodrguez, Miguel A. Molina-Cabello, Rafaela Bentez-Rochel, Ezequiel Lpez-Rubio |
| 2021 | IJCNN | Enhanced transfer learning model by image shifting on a square lattice for skin lesion malignancy assessment. | Karl Thurnhofer-Hemsi, Rosa Maza-Quiroga, Enrique Domnguez, Miguel A. Molina-Cabello, Ezequiel Lpez-Rubio |
| 2021 | IWANN | Classification of Images as Photographs or Paintings by Using Convolutional Neural Networks. | Jos Miguel Lpez-Rubio, Miguel A. Molina-Cabello, Gonzalo Ramos-Jimnez, Ezequiel Lpez-Rubio |
| 2021 | IWANN | Enforcing Morphological Information in Fully Convolutional Networks to Improve Cell Instance Segmentation in Fluorescence Microscopy Images. | Willard Zamora-Crdenas, Mauro Mendez, Sal Caldern Ramrez, Martin Vargas, Gerardo Monge, Steve Quirs, David A. Elizondo, Jordina Torrents-Barrena, Miguel A. Molina-Cabello |
| 2020 | ICIP | Deep Autoencoder Architectures For Foreground Object Detection In Video Sequences Based On Probabilistic Mixture Models. | Jorge Garca-Gonzlez, Miguel A. Molina-Cabello, Rafael M. Luque-Baena, Juan Miguel Ortiz-de-Lazcano-Lobato, Ezequiel Lpez-Rubio |
| 2020 | ICPR | Adaptive estimation of optimal color transformations for deep convolutional network based homography estimation. | Miguel A. Molina-Cabello, Jorge Garca-Gonzlez, Rafael Marcos Luque Baena, Karl Thurnhofer-Hemsi, Ezequiel Lpez-Rubio |
| 2020 | ICPR | Dealing with Scarce Labelled Data: Semi-supervised Deep Learning with Mix Match for Covid-19 Detection Using Chest X-ray Images. | Sal Caldern Ramrez, Raghvendra Giri, Shengxiang Yang, Armaghan Moemeni, Mario Umaa, David A. Elizondo, Jordina Torrents-Barrena, Miguel A. Molina-Cabello |
| 2020 | ICPR | The Impact of Linear Motion Blur on the Object Recognition Efficiency of Deep Convolutional Neural Networks. | Jos A. Rodrguez-Rodrguez, Miguel A. Molina-Cabello, Rafaela Bentez-Rochel, Ezequiel Lpez-Rubio |
| 2020 | ICPR | The Effect of Noise and Brightness on Convolutional Deep Neural Networks. | Jos A. Rodrguez-Rodrguez, Miguel A. Molina-Cabello, Rafaela Bentez-Rochel, Ezequiel Lpez-Rubio |
| 2020 | ICPR | The effect of image enhancement algorithms on convolutional neural networks. | Jos A. Rodrguez-Rodrguez, Miguel A. Molina-Cabello, Rafaela Bentez-Rochel, Ezequiel Lpez-Rubio |
| 2020 | ICPR | Performance of Deep Learning and Traditional Techniques in Single Image Super-Resolution of Noisy Images. | Karl Thurnhofer-Hemsi, Guillermo Ruiz-lvarez, Rafael Marcos Luque Baena, Miguel A. Molina-Cabello, Ezequiel Lpez-Rubio |
| 2019 | IWANN | Optimization of Convolutional Neural Network Ensemble Classifiers by Genetic Algorithms. | Miguel A. Molina-Cabello, Cristian Accino, Ezequiel Lpez-Rubio, Karl Thurnhofer-Hemsi |
| 2019 | IWANN | Infering Air Quality from Traffic Data Using Transferable Neural Network Models. | Miguel A. Molina-Cabello, Benjamin N. Passow, Enrique Domnguez, David A. Elizondo, Jolanta Obszynska |
| 2019 | IWINAC | Content Based Image Retrieval by Convolutional Neural Networks. | Safa Hamreras, Rafaela Bentez-Rochel, Bachir Boucheham, Miguel A. Molina-Cabello, Ezequiel Lpez-Rubio |
| 2019 | IWINAC | Deep Learning Networks with p-norm Loss Layers for Spatial Resolution Enhancement of 3D Medical Images. | Karl Thurnhofer-Hemsi, Ezequiel Lpez-Rubio, Nria Ro-Vellv, Miguel A. Molina-Cabello |
| 2018 | IJCNN | Road Pollution Estimation Using Static Cameras And Neural Networks. | Miguel A. Molina-Cabello, Rafael Marcos Luque Baena, Ezequiel Lpez-Rubio, Lipika Deka, Karl Thurnhofer-Hemsi |
| 2018 | IJCNN | A New Self-Organizing Neural Gas Model based on Bregman Divergences. | Esteban J. Palomo, Miguel A. Molina-Cabello, Ezequiel Lpez-Rubio, Rafael Marcos Luque Baena |
| 2018 | IJCNN | Super-resolution of 3D Magnetic Resonance Images by Random Shifting and Convolutional Neural Networks. | Karl Thurnhofer-Hemsi, Ezequiel Lpez-Rubio, Nria Ro-Vellv, Enrique Domnguez, Miguel A. Molina-Cabello |
| 2018 | IPMU | Foreground Detection Enhancement Using Pearson Correlation Filtering. | Rafael Marcos Luque Baena, Miguel A. Molina-Cabello, Ezequiel Lpez-Rubio, Enrique Domnguez |
| 2018 | WorldCIST | Blood Cell Classification Using the Hough Transform and Convolutional Neural Networks. | Miguel A. Molina-Cabello, Ezequiel Lpez-Rubio, Rafael M. Luque-Baena, Mara Jess Rodrguez-Espinosa, Karl Thurnhofer-Hemsi |
| 2017 | IJCNN | Neural controller for PTZ cameras based on nonpanoramic foreground detection. | Miguel A. Molina-Cabello, Ezequiel Lpez-Rubio, Rafael Marcos Luque Baena, Enrique Domnguez, Karl Thurnhofer-Hemsi |
| 2017 | IJCNN | Panoramic background modeling for PTZ cameras with competitive learning neural networks. | Karl Thurnhofer-Hemsi, Ezequiel Lpez-Rubio, Enrique Domnguez, Rafael Marcos Luque Baena, Miguel A. Molina-Cabello |
| 2017 | IWANN | Vehicle Classification in Traffic Environments Using the Growing Neural Gas. | Miguel A. Molina-Cabello, Rafael Marcos Luque Baena, Ezequiel Lpez-Rubio, Juan Miguel Ortiz-de-Lazcano-Lobato, Enrique Domnguez, Jos Muoz-Prez |
| 2017 | IWINAC | Vehicle Type Detection by Convolutional Neural Networks. | Miguel A. Molina-Cabello, Rafael Marcos Luque Baena, Ezequiel Lpez-Rubio, Karl Thurnhofer-Hemsi |