Zobrazeno 1 - 10
of 259
pro vyhledávání: '"Mauro Castelli"'
Publikováno v:
Emerging Science Journal, Vol 8, Iss 5, Pp 2003-2022 (2024)
This work explores the application of zero-shot prompting strategies for table question answering (TQA) in Portuguese, focusing specifically on the Text2SQL task. This task involves translating questions posed in natural language into Structured Quer
Externí odkaz:
https://doaj.org/article/f13f8bfcb89f41da8b04e12ed323c1f8
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Life sciences research and experimentation are resource-intensive, requiring extensive trials and considerable time. Often, experiments do not achieve their intended objectives, but progress is made through trial and error, eventually leadin
Externí odkaz:
https://doaj.org/article/7b00063ed3fd4aada27dcedc3d1913cf
Autor:
Cristiana Fiscone, Giovanni Sighinolfi, David Neil Manners, Lorenzo Motta, Greta Venturi, Ivan Panzera, Fulvio Zaccagna, Leonardo Rundo, Alessandra Lugaresi, Raffaele Lodi, Caterina Tonon, Mauro Castelli
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-11 (2024)
Abstract Multiple sclerosis (MS) is a progressive demyelinating disease impacting the central nervous system. Conventional Magnetic Resonance Imaging (MRI) techniques (e.g., T2w images) help diagnose MS, although they sometimes reveal non-specific le
Externí odkaz:
https://doaj.org/article/b715229596744fe69c4c6e3e5deca67f
Publikováno v:
Array, Vol 24, Iss , Pp 100368- (2024)
Accessing relational databases using natural language is a challenging task, with existing methods often suffering from poor domain generalization and high computational costs. In this study, we propose a novel approach that eliminates the training p
Externí odkaz:
https://doaj.org/article/62e6bac6c424491397566ec46f87288c
Publikováno v:
Emerging Science Journal, Vol 8, Iss 1, Pp 270-282 (2024)
This study proposes the use of Artificial Intelligence (AI) to automatize part of the legislative impact assessment process. In particular, the focus of this study is the automatic identification of administrative burdens from legislative documents.
Externí odkaz:
https://doaj.org/article/f982645c7cf64ace84db9e5fb7eb6925
Publikováno v:
IEEE Access, Vol 12, Pp 155136-155150 (2024)
This paper presents a novel methodology for enhancing Automatic Speech Recognition (ASR) performance by utilizing contrastive learning to filter synthetic audio data. We address the challenge of incorporating synthetic data into ASR training, especia
Externí odkaz:
https://doaj.org/article/198166fd446848a89cad4d39bdb02b75
Publikováno v:
Applied Sciences, Vol 14, Iss 20, p 9493 (2024)
Estimating the location of unmanned aerial vehicles (UAVs) within a global coordinate system can be achieved by correlating known world points with their corresponding image projections captured by the vehicle’s camera. Reducing the number of requi
Externí odkaz:
https://doaj.org/article/9e63e44035a544fbb81f4524d55c6c05
Autor:
Francisco Cruz, Mauro Castelli
Publikováno v:
Emerging Science Journal, Vol 7, Iss 5, Pp 1491-1500 (2023)
One of the main challenges when training or fine-tuning a machine learning model concerns the number of observations necessary to achieve satisfactory performance. While, in general, more training observations result in a better-performing model, col
Externí odkaz:
https://doaj.org/article/6d8b7a1827b649f5a722210a348dc617
Autor:
Cristiana Fiscone, Leonardo Rundo, Alessandra Lugaresi, David Neil Manners, Kieren Allinson, Elisa Baldin, Gianfranco Vornetti, Raffaele Lodi, Caterina Tonon, Claudia Testa, Mauro Castelli, Fulvio Zaccagna
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-16 (2023)
Abstract Multiple Sclerosis (MS) is an autoimmune demyelinating disease characterised by changes in iron and myelin content. These biomarkers are detectable by Quantitative Susceptibility Mapping (QSM), an advanced Magnetic Resonance Imaging techniqu
Externí odkaz:
https://doaj.org/article/8a86b56aa3c341ffad9f0bc94b82e966
Publikováno v:
Emerging Science Journal, Vol 7, Iss 4, Pp 1037-1051 (2023)
Some optimization problems are difficult to solve due to a considerable number of local optima, which may result in premature convergence of the optimization process. To address this problem, we propose a novel heuristic method for constructing a smo
Externí odkaz:
https://doaj.org/article/394a399fdd0f40739755823942dfc26b