Zobrazeno 1 - 10
of 1 901
pro vyhledávání: '"A. Fernández-Torres"'
Autor:
Pellicer-Valero, Oscar J., Fernández-Torres, Miguel-Ángel, Ji, Chaonan, Mahecha, Miguel D., Camps-Valls, Gustau
With climate change-related extreme events on the rise, high dimensional Earth observation data presents a unique opportunity for forecasting and understanding impacts on ecosystems. This is, however, impeded by the complexity of processing, visualiz
Externí odkaz:
http://arxiv.org/abs/2410.01770
Autor:
Camps-Valls, Gustau, Fernández-Torres, Miguel-Ángel, Cohrs, Kai-Hendrik, Höhl, Adrian, Castelletti, Andrea, Pacal, Aytac, Robin, Claire, Martinuzzi, Francesco, Papoutsis, Ioannis, Prapas, Ioannis, Pérez-Aracil, Jorge, Weigel, Katja, Gonzalez-Calabuig, Maria, Reichstein, Markus, Rabel, Martin, Giuliani, Matteo, Mahecha, Miguel, Popescu, Oana-Iuliana, Pellicer-Valero, Oscar J., Ouala, Said, Salcedo-Sanz, Sancho, Sippel, Sebastian, Kondylatos, Spyros, Happé, Tamara, Williams, Tristan
In recent years, artificial intelligence (AI) has deeply impacted various fields, including Earth system sciences. Here, AI improved weather forecasting, model emulation, parameter estimation, and the prediction of extreme events. However, the latter
Externí odkaz:
http://arxiv.org/abs/2406.20080
Autor:
Ji, Chaonan, Fincke, Tonio, Benson, Vitus, Camps-Valls, Gustau, Fernandez-Torres, Miguel-Angel, Gans, Fabian, Kraemer, Guido, Martinuzzi, Francesco, Montero, David, Mora, Karin, Pellicer-Valero, Oscar J., Robin, Claire, Soechting, Maximilian, Weynants, Melanie, Mahecha, Miguel D.
With climate extremes' rising frequency and intensity, robust analytical tools are crucial to predict their impacts on terrestrial ecosystems. Machine learning techniques show promise but require well-structured, high-quality, and curated analysis-re
Externí odkaz:
http://arxiv.org/abs/2406.18179
This PhD. Thesis concerns the study and development of hierarchical representations for spatio-temporal visual attention modeling and understanding in video sequences. More specifically, we propose two computational models for visual attention. First
Externí odkaz:
http://arxiv.org/abs/2308.05189
Autor:
Javier Fernández-Torres, Yessica Zamudio-Cuevas, Karina Martínez-Flores, Ambar López-Macay, Graciela Rosas-Alquicira, María Guadalupe Martínez-Zavaleta, Luis Esaú López-Jácome, Rafael Franco-Cendejas, Ernesto Roldan-Valadez
Publikováno v:
PeerJ, Vol 12, p e18560 (2024)
Background Diagnosing periprosthetic joint infection (PJI) remains a significant challenge for healthcare professionals. Commonly utilized inflammatory markers include erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and white blood ce
Externí odkaz:
https://doaj.org/article/da8ee498e92f43b9a3d5f04c581f1bdc
Autor:
Sánchez-Rivero, Marcelino, Gutiérrez-Fernández, Milagros, Fernández-Torres, Yakira, Gallego-Sosa, Clara
Publikováno v:
Gender in Management: An International Journal, 2023, Vol. 39, Issue 2, pp. 239-254.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/GM-04-2022-0147
Autor:
Ávila-García, Juan Manuel a, Fernández-Torres, Rut a, Sánchez-Ruíz, Rocío b, Moreno, Isabel María b, Aranda-Merino, Noemí a, ⁎, Ramos-Payán, María a, ⁎
Publikováno v:
In Microchemical Journal December 2024 207
Autor:
Elsa M. Orellano-Colon, Angelis Fernández-Torres, Nixmarie Figueroa-Alvira, Bernice Ortiz-Vélez, Nina L. Rivera-Rivera, Gabriela A. Torres-Ferrer, Rubén Martín-Payo
Publikováno v:
Disabilities, Vol 4, Iss 2, Pp 303-320 (2024)
The use of assistive technology (AT) devices enhances older adults’ function in daily activities. However, the lack of awareness of AT among potential AT users has been identified as a major barrier to its adoption. This study aimed to assess the q
Externí odkaz:
https://doaj.org/article/483b4192610e4b5f96196d02f0268998
Autor:
Prapas, Ioannis, Kondylatos, Spyros, Papoutsis, Ioannis, Camps-Valls, Gustau, Ronco, Michele, Fernández-Torres, Miguel-Ángel, Guillem, Maria Piles, Carvalhais, Nuno
Wildfire forecasting is of paramount importance for disaster risk reduction and environmental sustainability. We approach daily fire danger prediction as a machine learning task, using historical Earth observation data from the last decade to predict
Externí odkaz:
http://arxiv.org/abs/2111.02736
Autor:
Ruiz-Muñoz, María, Fernández-Torres, Raúl, Formosa, Cynthia, Gatt, Alfred, Pérez-Panero, Alberto José, Pérez-Belloso, Ana Juana, Martínez-Barrios, Francisco Javier, González-Sánchez, Manuel
Publikováno v:
In Primary Care Diabetes October 2024 18(5):525-532