Zobrazeno 1 - 10
of 3 789
pro vyhledávání: '"Guerrero, José"'
Autor:
Martín, Francisco, Soriano-Salvador, Enrique, Guerrero, José Miguel, Múzquiz, Gorka Guardiola, Manzanares, Juan Carlos, Rodríguez, Francisco J.
Social Robots need to be safe and reliable to share their space with humans. This paper reports on the first results of a research project that aims to create more safe and reliable, intelligent autonomous robots by investigating the implications and
Externí odkaz:
http://arxiv.org/abs/2407.06669
Autor:
Caron, Sascha, Dobreva, Nadezhda, Sánchez, Antonio Ferrer, Martín-Guerrero, José D., Odyurt, Uraz, Bazan, Roberto Ruiz de Austri, Wolffs, Zef, Zhao, Yue
High-Energy Physics experiments are facing a multi-fold data increase with every new iteration. This is certainly the case for the upcoming High-Luminosity LHC upgrade. Such increased data processing requirements forces revisions to almost every step
Externí odkaz:
http://arxiv.org/abs/2407.07179
Quantum machine learning, as an extension of classical machine learning that harnesses quantum mechanics, facilitates effiient learning from data encoded in quantum states. Training a quantum neural network typically demands a substantial labeled tra
Externí odkaz:
http://arxiv.org/abs/2405.18230
Autor:
Odyurt, Uraz, Dobreva, Nadezhda, Wolffs, Zef, Zhao, Yue, Sánchez, Antonio Ferrer, Bazan, Roberto Ruiz de Austri, Martín-Guerrero, José D., Varbanescu, Ana-Lucia, Caron, Sascha
Track reconstruction is a vital aspect of High-Energy Physics (HEP) and plays a critical role in major experiments. In this study, we delve into unexplored avenues for particle track reconstruction and hit clustering. Firstly, we enhance the algorith
Externí odkaz:
http://arxiv.org/abs/2405.17325
Autor:
Simen, Anton, Flores-Garrigos, Carlos, Hegade, Narendra N., Montalban, Iraitz, Vives-Gilabert, Yolanda, Michon, Eric, Zhang, Qi, Solano, Enrique, Martín-Guerrero, José D.
We propose digital-analog quantum kernels for enhancing the detection of complex features in the classification of images. We consider multipartite-entangled analog blocks, stemming from native Ising interactions in neutral-atom quantum processors, a
Externí odkaz:
http://arxiv.org/abs/2405.00548
Autor:
Pinto, Javier, Magri, Davide, Valentini, Paola, Palazon, Francisco, Heredia-Guerrero, Jose A., Lauciello, Simone, Barroso-Solares, Suset, Ceseracciu, Luca, Pompa, Pier Paolo, Athanassiou, Athanassia, Fragouli, Despina
Publikováno v:
ACS Applied Materials & Interfaces, 2018, 10, 18, 16095-16104
A new and straightforward single-step route to decorate melamine foams with silver nanoparticles (ME/Ag) is proposed.
Externí odkaz:
http://arxiv.org/abs/2402.04988
Publikováno v:
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 3702-3705) 2021
From a non-central panorama, 3D lines can be recovered by geometric reasoning. However, their sensitivity to noise and the complex geometric modeling required has led these panoramas being very little investigated. In this work we present a novel app
Externí odkaz:
http://arxiv.org/abs/2402.01466
Autor:
Berenguel-Baeta, Bruno, Andre, Antoine N., Caron, Guillaume, Bermudez-Cameo, Jesus, Guerrero, Jose J.
Publikováno v:
IEEE/CVF Conference on Computer Vision and Pattern Recognition pp. 6444-6447, 2023
In this article we present a visual gyroscope based on equirectangular panoramas. We propose a new pipeline where we take advantage of combining three different methods to obtain a robust and accurate estimation of the attitude of the camera. We quan
Externí odkaz:
http://arxiv.org/abs/2402.01461
Autor:
Berenguel-Baeta, Bruno, Santos-Villafranca, Maria, Bermudez-Cameo, Jesus, Perez-Yus, Alejandro, Guerrero, Jose J.
Convolution kernels are the basic structural component of convolutional neural networks (CNNs). In the last years there has been a growing interest in fisheye cameras for many applications. However, the radially symmetric projection model of these ca
Externí odkaz:
http://arxiv.org/abs/2402.01456
Publikováno v:
Data in Brief 2022, Volume 43, pp. 108375
Omnidirectional images are one of the main sources of information for learning based scene understanding algorithms. However, annotated datasets of omnidirectional images cannot keep the pace of these learning based algorithms development. Among the
Externí odkaz:
http://arxiv.org/abs/2401.17075