Zobrazeno 1 - 10
of 4 171
pro vyhledávání: '"P. Soda"'
Autor:
Francesconi, Arianna, di Biase, Lazzaro, Cappetta, Donato, Rebecchi, Fabio, Soda, Paolo, Sicilia, Rosa, Guarrasi, Valerio
Alzheimer's disease (AD) poses significant global health challenges due to its increasing prevalence and associated societal costs. Early detection and diagnosis of AD are critical for delaying progression and improving patient outcomes. Traditional
Externí odkaz:
http://arxiv.org/abs/2410.10374
Autor:
White, Derek D., Zhang, Shunxing, Soda, Barbara, Kempf, Achim, Struppa, Daniele C., Jordan, Andrew N., Howell, John C.
We utilize a method using frequency combs to construct waves that feature superoscillations - local regions of the wave that exhibit a change in phase that the bandlimits of the wave should not otherwise allow. This method has been shown to create su
Externí odkaz:
http://arxiv.org/abs/2410.05399
We study conversion processes between gravitons and dark photons and reveal the effects of dark photons on the polarization of gravitational waves. Considering cosmological dark magnetic fields, we investigate the evolution of the intensity and polar
Externí odkaz:
http://arxiv.org/abs/2409.10471
Endoscopic surgery relies on two-dimensional views, posing challenges for surgeons in depth perception and instrument manipulation. While Monocular Visual Simultaneous Localization and Mapping (MVSLAM) has emerged as a promising solution, its impleme
Externí odkaz:
http://arxiv.org/abs/2408.03078
Identifying risky driving behavior in real-world situations is essential for the safety of both drivers and pedestrians. However, integrating natural language models in this field remains relatively untapped. To address this, we created a novel multi
Externí odkaz:
http://arxiv.org/abs/2408.01682
Autor:
Guarrasi, Valerio, Aksu, Fatih, Caruso, Camillo Maria, Di Feola, Francesco, Rofena, Aurora, Ruffini, Filippo, Soda, Paolo
Deep learning has revolutionized biomedical research by providing sophisticated methods to handle complex, high-dimensional data. Multimodal deep learning (MDL) further enhances this capability by integrating diverse data types such as imaging, textu
Externí odkaz:
http://arxiv.org/abs/2408.02686
Autor:
Zhang, Chongsheng, Almpanidis, George, Fan, Gaojuan, Deng, Binquan, Zhang, Yanbo, Liu, Ji, Kamel, Aouaidjia, Soda, Paolo, Gama, João
Long-tailed data is a special type of multi-class imbalanced data with a very large amount of minority/tail classes that have a very significant combined influence. Long-tailed learning aims to build high-performance models on datasets with long-tail
Externí odkaz:
http://arxiv.org/abs/2408.00483
Handling missing values in tabular datasets presents a significant challenge in training and testing artificial intelligence models, an issue usually addressed using imputation techniques. Here we introduce "Not Another Imputation Method" (NAIM), a n
Externí odkaz:
http://arxiv.org/abs/2407.11540
Autor:
Ruffini, Filippo, Tronchin, Lorenzo, Wu, Zhuoru, Chen, Wenting, Soda, Paolo, Shen, Linlin, Guarrasi, Valerio
In the fight against the COVID-19 pandemic, leveraging artificial intelligence to predict disease outcomes from chest radiographic images represents a significant scientific aim. The challenge, however, lies in the scarcity of large, labeled datasets
Externí odkaz:
http://arxiv.org/abs/2405.13771
Autor:
F. Prata, F. Esperto, A. Civitella, P. Tuzzolo, E. Cordelli, R. Sicilia, M. Merone, P. Soda, G. Muto, R.M. Scarpa, R. Papalia
Publikováno v:
European Urology Open Science, Vol 20, Iss , Pp S48-S49 (2020)
Externí odkaz:
https://doaj.org/article/a9421277ad6f4f40a500249789684196
