Zobrazeno 1 - 10
of 1 458
pro vyhledávání: '"P. Scarpellini"'
Autor:
Tsesmelis, Theodore, Palmieri, Luca, Khoroshiltseva, Marina, Islam, Adeela, Elkin, Gur, Shahar, Ofir Itzhak, Scarpellini, Gianluca, Fiorini, Stefano, Ohayon, Yaniv, Alali, Nadav, Aslan, Sinem, Morerio, Pietro, Vascon, Sebastiano, Gravina, Elena, Napolitano, Maria Cristina, Scarpati, Giuseppe, Zuchtriegel, Gabriel, Spühler, Alexandra, Fuchs, Michel E., James, Stuart, Ben-Shahar, Ohad, Pelillo, Marcello, Del Bue, Alessio
This paper proposes the RePAIR dataset that represents a challenging benchmark to test modern computational and data driven methods for puzzle-solving and reassembly tasks. Our dataset has unique properties that are uncommon to current benchmarks for
Externí odkaz:
http://arxiv.org/abs/2410.24010
Publikováno v:
Journal of Maps, Vol 16, Iss 2, Pp 357-362 (2020)
Land capability classification is based on chemical and physical properties of soils for agricultural purposes. Objective of this study is the realization of the land capability map in the Vernazza catchment, an historically terraced landscape in the
Externí odkaz:
https://doaj.org/article/8c426e490dc04f7bbd78c5f29a18fc9b
Autor:
Scarpellini, Gianluca, Fiorini, Stefano, Giuliari, Francesco, Morerio, Pietro, Del Bue, Alessio
Reassembly tasks play a fundamental role in many fields and multiple approaches exist to solve specific reassembly problems. In this context, we posit that a general unified model can effectively address them all, irrespective of the input data type
Externí odkaz:
http://arxiv.org/abs/2402.19302
Autor:
V. Spagnuolo, M. Guffanti, L. Galli, A. Poli, P. Rovere Querini, M. Ripa, M. Clementi, P. Scarpellini, A. Lazzarin, M. Tresoldi, L. Dagna, A. Zangrillo, F. Ciceri, A. Castagna, COVID-BioB study group
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-1 (2021)
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Externí odkaz:
https://doaj.org/article/1403d3d1860b434f93c1a30969356432
Autor:
Elisa Roberti, Francesca Scarpellini, Rita Campi, Michele Giardino, Michele Zanetti, Antonio Clavenna, TransiDEA Group Maurizio Bonati
Publikováno v:
BMC Psychiatry, Vol 24, Iss 1, Pp 1-10 (2024)
Abstract Background For Attention Deficit/Hyperactivity Disorder (ADHD) youth transitioning from child to adult services, protocols that guide the transition process are essential. While some guidelines are available, they do not always consider the
Externí odkaz:
https://doaj.org/article/5f6d410856fe4c64a0d38a3e9ab3e038
Autor:
Aline Scarpellini Campos, Ana Claúdia Franco, Fernanda M. Godinho, Rosana Huff, Darlan S. Candido, Jader da Cruz Cardoso, Xinyi Hua, Ingra M. Claro, Paola Morais, Carolina Franceschina, Thales de Lima Bermann, Franciellen Machado dos Santos, Milena Bauermann, Tainá Machado Selayaran, Amanda Pellenz Ruivo, Cristiane Santin, Juciane Bonella, Carla Rodenbusch, José Carlos Ferreira, Scott C. Weaver, Vilar Ricardo Gewehr, Gabriel Luz Wallau, William M. de Souza, Richard Steiner Salvato
Publikováno v:
Emerging Infectious Diseases, Vol 30, Iss 9, Pp 1834-1840 (2024)
Western equine encephalitis virus (WEEV) is a mosquitoborne virus that reemerged in December 2023 in Argentina and Uruguay, causing a major outbreak. We investigated the outbreak using epidemiologic, entomological, and genomic analyses, focusing on W
Externí odkaz:
https://doaj.org/article/128a403fa6bf45b3bcfdcfb02ea74966
Autor:
Scarpellini, Gianluca, Konyushkova, Ksenia, Fantacci, Claudio, Paine, Tom Le, Chen, Yutian, Denil, Misha
This paper describes $\pi2\text{vec}$, a method for representing behaviors of black box policies as feature vectors. The policy representations capture how the statistics of foundation model features change in response to the policy behavior in a tas
Externí odkaz:
http://arxiv.org/abs/2306.09800
Positional reasoning is the process of ordering unsorted parts contained in a set into a consistent structure. We present Positional Diffusion, a plug-and-play graph formulation with Diffusion Probabilistic Models to address positional reasoning. We
Externí odkaz:
http://arxiv.org/abs/2303.11120
Object detectors often experience a drop in performance when new environmental conditions are insufficiently represented in the training data. This paper studies how to automatically fine-tune a pre-existing object detector while exploring and acquir
Externí odkaz:
http://arxiv.org/abs/2302.10624
When an object detector is deployed in a novel setting it often experiences a drop in performance. This paper studies how an embodied agent can automatically fine-tune a pre-existing object detector while exploring and acquiring images in a new envir
Externí odkaz:
http://arxiv.org/abs/2302.03566