Zobrazeno 1 - 10
of 4 178
pro vyhledávání: '"Tosato, A"'
Autor:
Stehouwer, Lucas E. A., Yu, Cécile X., van Straaten, Barnaby, Tosato, Alberto, John, Valentin, Esposti, Davide Degli, Elsayed, Asser, Costa, Davide, Oosterhout, Stefan D., Hendrickx, Nico W., Veldhorst, Menno, Borsoi, Francesco, Scappucci, Giordano
Disorder in the heterogeneous material stack of semiconductor spin qubit systems introduces noise that compromises quantum information processing, posing a challenge to coherently control large-scale quantum devices. Here, we exploit low-disorder epi
Externí odkaz:
http://arxiv.org/abs/2411.11526
High-performance computing (HPC) and supercomputing are critical in Artificial Intelligence (AI) research, development, and deployment. The extensive use of supercomputers for training complex AI models, which can take from days to months, raises sig
Externí odkaz:
http://arxiv.org/abs/2409.17368
Robustly estimating energy consumption in High-Performance Computing (HPC) is essential for assessing the energy footprint of modern workloads, particularly in fields such as Artificial Intelligence (AI) research, development, and deployment. The ext
Externí odkaz:
http://arxiv.org/abs/2409.04941
Publikováno v:
Pattern Recognition Letters Volume 177, January 2024, Pages 164 168
Studies in human human interaction have introduced the concept of F formation to describe the spatial arrangement of participants during social interactions. This paper has two objectives. It aims at detecting F formations in video sequences and pred
Externí odkaz:
http://arxiv.org/abs/2408.16380
Publikováno v:
15th European Conference on Synthetic Aperture Radar, April 23 26, 2024, Munich, Germany
Remote sensing visual question answering (RSVQA) has been involved in several research in recent years, leading to an increase in new methods. RSVQA automatically extracts information from satellite images, so far only optical, and a question to auto
Externí odkaz:
http://arxiv.org/abs/2408.15642
Autor:
Tosato, Lucrezia, Boussaid, Hichem, Weissgerber, Flora, Kurtz, Camille, Wendling, Laurent, Lobry, Sylvain
Visual Question Answering for Remote Sensing (RSVQA) is a task that aims at answering natural language questions about the content of a remote sensing image. The visual features extraction is therefore an essential step in a VQA pipeline. By incorpor
Externí odkaz:
http://arxiv.org/abs/2407.08669
Language Models (LMs) have achieved impressive performance on various linguistic tasks, but their relationship to human language processing in the brain remains unclear. This paper examines the gaps and overlaps between LMs and the brain at different
Externí odkaz:
http://arxiv.org/abs/2407.04680
Autor:
Tosato, Giulio, Shehata, Abdelrahman, Janssen, Joshua, Kamp, Kees, Jati, Pramatya, Stowell, Dan
This study investigates the potential of automated deep learning to enhance the accuracy and efficiency of multi-class classification of bird vocalizations, compared against traditional manually-designed deep learning models. Using the Western Medite
Externí odkaz:
http://arxiv.org/abs/2311.04945
Autor:
Stefano Cacciatore, Anna Maria Martone, Francesca Ciciarello, Vincenzo Galluzzo, Giordana Gava, Claudia Massaro, Riccardo Calvani, Matteo Tosato, Emanuele Marzetti, Francesco Landi, The Lookup 8+ Study Group
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Diabetes is a prevalent metabolic condition with substantial health and economic impacts. Therefore, effective and accessible indicators are essential for early detection and prevention. This study investigates the link between the waist-to-
Externí odkaz:
https://doaj.org/article/ba5b712ca07c4fec8f15991c7f4fdee8
Autor:
Marco Floridia, Marina Giuliano, Liliana Elena Weimer, Maria Rosa Ciardi, Piergiuseppe Agostoni, Paolo Palange, Patrizia Rovere Querini, Silvia Zucco, Matteo Tosato, Aldo Lo Forte, Paolo Bonfanti, Donato Lacedonia, Emanuela Barisione, Stefano Figliozzi, Paola Andreozzi, Cecilia Damiano, Flavia Pricci, Graziano Onder, the I. S. S. Long-COVID Study Group
Publikováno v:
BMC Medicine, Vol 22, Iss 1, Pp 1-11 (2024)
Abstract Background Long-COVID symptoms remain incompletely defined due to a large heterogeneity in the populations studied, case definitions, and settings of care. The aim of this study was to assess, in patients accessing care for Long-COVID, the p
Externí odkaz:
https://doaj.org/article/27a513781e7b40259d6402f4e44219a0