A Bayesian model for brain tumor classification using clinical-based features. - Tomás Martínez-Cortés; Miguel Angel Fernandez-Torres; Amaya Jimenez-Moreno; Iván González-Díaz 001; Fernando Díaz-de-María; Juan Adan Guzmán-De-Villoria; Pilar Fernández (ICIP, 2014)

A probabilistic topic approach for context-aware visual attention modeling. - Miguel Angel Fernandez-Torres; Iván González-Díaz 001; Fernando Díaz-de-María (CBMI, 2016)

Exploiting visual saliency for assessing the impact of car commercials upon viewers. - Fernando Fernández Martínez; René Arnulfo García-Hernández; Miguel Angel Fernandez-Torres; Iván González-Díaz 001; Álvaro García-Faura; Fernando Díaz-de-María (Multim. Tools Appl., 2018)

Enriched dermoscopic-structure-based cad system for melanoma diagnosis. - Javier López-Labraca; Miguel Angel Fernandez-Torres; Iván González-Díaz 001; Fernando Díaz-de-María; Ángel Pizarro (Multim. Tools Appl., 2018)

Interpretable Global-Local Dynamics for the Prediction of Eye Fixations in Autonomous Driving Scenarios. - Javier Martínez-Cebrián; Miguel Angel Fernandez-Torres; Fernando Díaz-de-María (IEEE Access, 2020)

Probabilistic Topic Model for Context-Driven Visual Attention Understanding. - Miguel Angel Fernandez-Torres; Iván González-Díaz 001; Fernando Díaz-de-María (IEEE Trans. Circuits Syst. Video Technol., 2020)

Deep Learning Methods for Daily Wildfire Danger Forecasting. - Ioannis Prapas; Spyros Kondylatos; Ioannis Papoutsis; Gustau Camps-Valls; Michele Ronco; Miguel-Ángel Fernández-Torres; Maria Piles Guillem; Nuno Carvalhais (CoRR, 2021)

Hierarchical Representations for Spatio-Temporal Visual Attention Modeling and Understanding. - Miguel-Ángel Fernández-Torres (CoRR, 2023)

Assessing the Impact of Using Short Videos for Teaching at Higher Education: Empirical Evidence From Log-Files in a Learning Management System. - Valero Laparra; Adrián Pérez-Suay; María Piles; Jordi Muñoz-Marí; Julia Amorós-López; Roberto Fernandez-Moran; Miguel-Ángel Fernández-Torres; José E. Adsuara (Rev. Iberoam. de Tecnol. del Aprendiz., 2023)

Recent Trends Challenges and Limitations of Explainable AI in Remote Sensing. - Adrian Höhl; Ivica Obadic; Miguel-Ángel Fernández-Torres; Dário A. B. Oliveira; Xiao Xiang Zhu 001 (XAI4CV, 2024)

Opening the Black-Box: A Systematic Review on Explainable AI in Remote Sensing. - Adrian Höhl; Ivica Obadic; Miguel-Ángel Fernández-Torres; Hiba Najjar; Dário A. B. Oliveira; Zeynep Akata; Andreas Dengel 001; Xiao Xiang Zhu 001 (CoRR, 2024)

DeepExtremeCubes: Integrating Earth system spatio-temporal data for impact assessment of climate extremes. - Chaonan Ji; Tonio Fincke; Vitus Benson; Gustau Camps-Valls; Miguel-Ángel Fernández-Torres; Fabian Gans; Guido Kraemer; Francesco Martinuzzi; David Montero 001; Karin Mora; Oscar J. Pellicer-Valero; Claire Robin; et al. (CoRR, 2024)

AI for Extreme Event Modeling and Understanding: Methodologies and Challenges. - Gustau Camps-Valls; Miguel-Ángel Fernández-Torres; Kai-Hendrik Cohrs; Adrian Höhl; Andrea Castelletti; Aytac Pacal; Claire Robin; Francesco Martinuzzi; Ioannis Papoutsis; Ioannis Prapas; Jorge Pérez-Aracil; Katja Weigel; et al. (CoRR, 2024)

Explainable Earth Surface Forecasting under Extreme Events. - Oscar J. Pellicer-Valero; Miguel-Ángel Fernández-Torres; Chaonan Ji; Miguel D. Mahecha; Gustau Camps-Valls (CoRR, 2024)

Deep Learning With Noisy Labels for Spatiotemporal Drought Detection. - Jordi Cortés-Andrés; Miguel-Ángel Fernández-Torres; Gustau Camps-Valls (IEEE Trans. Geosci. Remote. Sens., 2024)

Calibration and uncertainty quantification for deep learning-based drought detection. - Mengxue Zhang; Miguel-Ángel Fernández-Torres; Kai-Hendrik Cohrs; Gustau Camps-Valls (Int. J. Appl. Earth Obs. Geoinformation, 2025)