Zobrazeno 1 - 10
of 36 948
pro vyhledávání: '"Nardi A"'
Autor:
Nardi, Davide, Lamon, Edoardo, Beber, Luca, Fontanelli, Daniele, Saveriano, Matteo, Palopoli, Luigi
The introduction of artificial intelligence and robotics in telehealth is enabling personalised treatment and supporting teleoperated procedures such as lung ultrasound, which has gained attention during the COVID-19 pandemic. Although fully autonomo
Externí odkaz:
http://arxiv.org/abs/2409.17395
Autor:
Nardi, Alfonso, Morandi, Andrea, Pierrat, Romain, Goetschy, Arthur, Li, Xuanchen, Scheffold, Frank, Grange, Rachel
Nonlinear disordered media uniquely combine multiple scattering and second-harmonic generation. Here, we investigate the statistical properties of the nonlinear light generated within such media. We report super-Rayleigh statistics of the second-harm
Externí odkaz:
http://arxiv.org/abs/2409.05488
Autor:
Argenziano, Francesco, Brienza, Michele, Suriani, Vincenzo, Nardi, Daniele, Bloisi, Domenico D.
Task planning for robots in real-life settings presents significant challenges. These challenges stem from three primary issues: the difficulty in identifying grounded sequences of steps to achieve a goal; the lack of a standardized mapping between h
Externí odkaz:
http://arxiv.org/abs/2408.17379
Autor:
Hashemipour-Nazari, Marzieh, Nardi-Dei, Andrea, Goossens, Kees, Balatsoukas-Stimming, Alexios
This paper presents the hardware implementation of two variants of projection-aggregation-based decoding of Reed-Muller (RM) codes, namely unique projection aggregation (UPA) and collapsed projection aggregation (CPA). Our study focuses on introducin
Externí odkaz:
http://arxiv.org/abs/2408.10850
Federated Learning (FL) is a pivotal approach in decentralized machine learning, especially when data privacy is crucial and direct data sharing is impractical. While FL is typically associated with supervised learning, its potential in unsupervised
Externí odkaz:
http://arxiv.org/abs/2408.10664
Autor:
Brienza, Michele, Argenziano, Francesco, Suriani, Vincenzo, Bloisi, Domenico D., Nardi, Daniele
Large Language Models (LLMs) and Visual Language Models (VLMs) are attracting increasing interest due to their improving performance and applications across various domains and tasks. However, LLMs and VLMs can produce erroneous results, especially w
Externí odkaz:
http://arxiv.org/abs/2408.05478
Publikováno v:
Journal of Experimental Pharmacology, Vol Volume 13, Pp 33-47 (2021)
Michelle N Levitan,1,2 Marcelo Papelbaum,2 Mauro G Carta,3 Jose C Appolinario,1 Antonio E Nardi1 1Psychiatry Institute/Federal University of Rio de Janeiro, Rio de Janeiro, Brazil; 2Eating Disorders Department/Sheba Medical Center, Ramat Gan, Israel;
Externí odkaz:
https://doaj.org/article/8b98484051da464b93b8641fd82fe640
We study tetraquarks in large $N$ QCD with heavy quarks, in the domain where non-relativistic quantum mechanics offers an adequate approximation. Within the regime of validity of the Born-Oppenheimer approximation, we systematically study and explici
Externí odkaz:
http://arxiv.org/abs/2407.18298
The hadronic vacuum polarization contribution to $(g-2)_\mu$ can be determined via dispersive methods from $e^+e^-\to\;$hadrons data. We propose a novel approach to measure the hadronic cross section $\sigma_{\mathrm{had}}$ as an alternative to the i
Externí odkaz:
http://arxiv.org/abs/2407.15941
Publikováno v:
Crop Protection, Volume 184, October 2024, 106848
The use of deep learning methods for precision farming is gaining increasing interest. However, collecting training data in this application field is particularly challenging and costly due to the need of acquiring information during the different gr
Externí odkaz:
http://arxiv.org/abs/2407.14119