Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Ignacio Heredia"'
Autor:
Miriam Cobo, Edgard Relaño de la Guía, Ignacio Heredia, Fernando Aguilar, Lara Lloret-Iglesias, Daniel García, Silvia Yuste, Emma Recio-Fernández, Patricia Pérez-Matute, M. José Motilva, M. Victoria Moreno-Arribas, Begoña Bartolomé
Publikováno v:
Heliyon, Vol 10, Iss 15, Pp e35689- (2024)
Estimation of wine components’ intake (polyphenols, alcohol, etc.) through Food Frequency Questionnaires (FFQs) may be particularly inaccurate. This paper reports the development of a deep learning (DL) method to determine red wine volume from sing
Externí odkaz:
https://doaj.org/article/8608c1486a4c493a8200c11b55ebd316
Autor:
Miriam Cobo, Francisco Pérez-Rojas, Constanza Gutiérrez-Rodríguez, Ignacio Heredia, Patricio Maragaño-Lizama, Francisca Yung-Manriquez, Lara Lloret Iglesias, José A. Vega
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-8 (2023)
Abstract Coronary artery tortuosity is usually an undetected condition in patients undergoing coronary angiography. This condition requires a longer examination by the specialist to be detected. Yet, detailed knowledge of the morphology of coronary a
Externí odkaz:
https://doaj.org/article/d815f88031a845559e63f62c243dcf3a
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-19 (2023)
Abstract In this work the applicability of an ensemble of population and machine learning models to predict the evolution of the COVID-19 pandemic in Spain is evaluated, relying solely on public datasets. Firstly, using only incidence data, we traine
Externí odkaz:
https://doaj.org/article/39fe49762b0a4f279a81b05e86cad29b
Autor:
Miriam Cobo, Ignacio Heredia, Fernando Aguilar, Lara Lloret Iglesias, Daniel García, Begoña Bartolomé, M. Victoria Moreno-Arribas, Silvia Yuste, Patricia Pérez-Matute, Maria-Jose Motilva
Publikováno v:
Heliyon, Vol 8, Iss 9, Pp e10557- (2022)
In this paper, we present a method to determine the volume of wine in different types of glass liquid containers from a single-view image. The proposed model predicts red wine volume from a photograph of the glass containing the wine. Experimental re
Externí odkaz:
https://doaj.org/article/811c3cf8046d42e09c504feee65d89cd
Autor:
Miriam Cobo, Francisco Pérez-Rojas, Constanza Gutiérrez-Rodríguez, Ignacio Heredia, Patricio Maragaño-Lizama, Francisca Yung-Manriquez, Lara Lloret Iglesias, José A. Vega
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-1 (2023)
Externí odkaz:
https://doaj.org/article/299cf99c6d144a938acd1ef991f327e7
Autor:
Díaz, Judith Sáinz-Pardo, Castrillo, María, Bartok, Juraj, Cachá, Ignacio Heredia, Ondík, Irina Malkin, Martynovskyi, Ivan, Alibabaei, Khadijeh, Berberi, Lisana, Kozlov, Valentin, García, Álvaro López
The increasing generation of data in different areas of life, such as the environment, highlights the need to explore new techniques for processing and exploiting data for useful purposes. In this context, artificial intelligence techniques, especial
Externí odkaz:
http://arxiv.org/abs/2408.05761
Autor:
Alvaro Lopez Garcia, Jesus Marco De Lucas, Marica Antonacci, Wolfgang Zu Castell, Mario David, Marcus Hardt, Lara Lloret Iglesias, Germen Molto, Marcin Plociennik, Viet Tran, Andy S. Alic, Miguel Caballer, Isabel Campos Plasencia, Alessandro Costantini, Stefan Dlugolinsky, Doina Cristina Duma, Giacinto Donvito, Jorge Gomes, Ignacio Heredia Cacha, Keiichi Ito, Valentin Y. Kozlov, Giang Nguyen, Pablo Orviz Fernandez, Zdenek Sustr, Pawel Wolniewicz
Publikováno v:
IEEE Access, Vol 8, Pp 18681-18692 (2020)
In this paper we propose a distributed architecture to provide machine learning practitioners with a set of tools and cloud services that cover the whole machine learning development cycle: ranging from the models creation, training, validation and t
Externí odkaz:
https://doaj.org/article/39de787ae5514e57996e126117d4770b
Deep Learning has recently emerged as a perfect prognosis downscaling technique to compute high-resolution fields from large-scale coarse atmospheric data. Despite their promising results to reproduce the observed local variability, they are based on
Externí odkaz:
http://arxiv.org/abs/2305.00974
Autor:
Cacha, Ignacio Heredia, Díaz, Judith Sainz-Pardo, Melguizo, María Castrillo, García, Álvaro López
In this work we evaluate the applicability of an ensemble of population models and machine learning models to predict the near future evolution of the COVID-19 pandemic, with a particular use case in Spain. We rely solely in open and public datasets,
Externí odkaz:
http://arxiv.org/abs/2207.05753
Autor:
Madrazo, Celia Fernández, Cacha, Ignacio Heredia, Iglesias, Lara Lloret, de Lucas, Jesús Marco
The application of deep learning techniques using convolutional neural networks to the classification of particle collisions in High Energy Physics is explored. An intuitive approach to transform physical variables, like momenta of particles and jets
Externí odkaz:
http://arxiv.org/abs/1708.07034