Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Javier Resano"'
Autor:
Maite Aramendía, Diego Leite, Javier Resano, Martín Resano, Kharmen Billimoria, Heidi Goenaga-Infante
Publikováno v:
Nanomaterials, Vol 13, Iss 17, p 2392 (2023)
This paper describes methodology based on the application of isotope dilution (ID) in single-particle inductively coupled plasma time-of-flight mass spectrometry (spICP-ToFMS) mode for the mass determination (and sizing) of silver nanoparticles (AgNP
Externí odkaz:
https://doaj.org/article/0d518662cd42404ea832b9c0f287fc1f
Publikováno v:
Remote Sensing, Vol 12, Iss 3, p 534 (2020)
Machine learning techniques are widely used for pixel-wise classification of hyperspectral images. These methods can achieve high accuracy, but most of them are computationally intensive models. This poses a problem for their implementation in low-po
Externí odkaz:
https://doaj.org/article/ff01caa6a0cc407fbe7891499a86078a
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2010 (2010)
Hyperspectral imaging is a new emerging technology in remote sensing which generates hundreds of images, at different wavelength channels, for the same area on the surface of the Earth. Over the last years, many algorithms have been developed with th
Externí odkaz:
https://doaj.org/article/e4ca0e0da5394683b907e32b7b932f37
Autor:
M. Carmen García-Poyo, Sylvain Bérail, Anne Laure Ronzani, Luis Rello, Elena García-González, Flávio V. Nakadi, Maite Aramendía, Javier Resano, Martín Resano, Christophe Pécheyran
Publikováno v:
Journal of Analytical Atomic Spectrometry. 38:229-242
Information about Cu fractionation and Cu isotopic composition can be paramount when investigating Wilson's disease (WD). This information can provide a better understanding of the metabolism of Cu. Most importantly, it may provide an easy way to dia
Autor:
Javier Plaza, Mercedes E. Paoletti, Antonio Plaza, Juan M. Haut, Adrián Alcolea, Javier Resano
Convolutional neural networks (CNNs) have proven to be very efficient for the analysis of remote sensing (RS) images. Due to the inherent complexity of extracting features from these images, along with the increasing amount of data to be processed (a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c4ef5bab8693f09f8fef45902402d372
http://zaguan.unizar.es/record/119879
http://zaguan.unizar.es/record/119879
Machine learning techniques, and specifically neural networks, have proved to be very useful tools for image classification tasks. Nevertheless, measuring the reliability of these networks and calibrating them accurately are very complex. This is eve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3adfbd0f61e84932961031d1c6c19f66
http://zaguan.unizar.es/record/121191
http://zaguan.unizar.es/record/121191
Autor:
Maite Aramendía, Juan Carlos García-Mesa, Elisa Vereda Alonso, Raúl Garde, Antonio Bazo, Javier Resano, Martín Resano
Publikováno v:
Analytica chimica acta. 1205
This paper presents a novel approach, based on the standard addition method, for overcoming the matrix effects that often hamper the accurate characterization of nanoparticles (NPs) in complex samples via single particle inductively coupled plasma ma
Autor:
Javier Resano, Adrián Alcolea
Publikováno v:
Zaguán: Repositorio Digital de la Universidad de Zaragoza
Universidad de Zaragoza
Electronics
Volume 10
Issue 3
Zaguán. Repositorio Digital de la Universidad de Zaragoza
instname
Electronics, Vol 10, Iss 314, p 314 (2021)
Universidad de Zaragoza
Electronics
Volume 10
Issue 3
Zaguán. Repositorio Digital de la Universidad de Zaragoza
instname
Electronics, Vol 10, Iss 314, p 314 (2021)
A decision tree is a well-known machine learning technique. Recently their popularity has increased due to the powerful Gradient Boosting ensemble method that allows to gradually increasing accuracy at the cost of executing a large number of decision
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7d9a70da932f95546406d7c510929403
http://zaguan.unizar.es/record/99722
http://zaguan.unizar.es/record/99722
Publikováno v:
Zaguán. Repositorio Digital de la Universidad de Zaragoza
Consejo Superior de Investigaciones Científicas (CSIC)
Consejo Superior de Investigaciones Científicas (CSIC)
Estimatabion of wave agitation plays a key role in predicting natural disasters, path optimization and secure harbor operation. The Spanish agency Puertos del Estado (PdE) has several oceanographic measure networks equipped with sensors for different
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7bfeabf2c79c9c1804f9692790fa2d1a
http://zaguan.unizar.es/record/109075
http://zaguan.unizar.es/record/109075
Publikováno v:
Zaguán. Repositorio Digital de la Universidad de Zaragoza
instname
instname
Deep neural networks (DNNs) are increasing their presence in a wide range of applications, and their computationally intensive and memory-demanding nature poses challenges, especially for embedded systems. Pruning techniques turn DNN models into spar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::db3bcd35420dd94b74c1ae407d6777d2
http://zaguan.unizar.es/record/106589
http://zaguan.unizar.es/record/106589