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pro vyhledávání: '"Barbano P"'
We present a way to learn novel concepts by only using their textual description. We call this method Knowledge Transfer. Similarly to human perception, we leverage cross-modal interaction to introduce new concepts. We hypothesize that in a pre-train
Externí odkaz:
http://arxiv.org/abs/2411.15611
Autor:
Sabanza-Gil, Víctor, Barbano, Riccardo, Gutiérrez, Daniel Pacheco, Luterbacher, Jeremy S., Hernández-Lobato, José Miguel, Schwaller, Philippe, Roch, Loïc
Multi-fidelity Bayesian Optimization (MFBO) is a promising framework to speed up materials and molecular discovery as sources of information of different accuracies are at hand at increasing cost. Despite its potential use in chemical tasks, there is
Externí odkaz:
http://arxiv.org/abs/2410.00544
Autor:
Ciranni, Massimiliano, Molinaro, Luca, Barbano, Carlo Alberto, Fiandrotti, Attilio, Murino, Vittorio, Pastore, Vito Paolo, Tartaglione, Enzo
In the last few years, due to the broad applicability of deep learning to downstream tasks and end-to-end training capabilities, increasingly more concerns about potential biases to specific, non-representative patterns have been raised. Many works f
Externí odkaz:
http://arxiv.org/abs/2408.09570
Deep Learning (DL) in neuroimaging has become increasingly relevant for detecting neurological conditions and neurodegenerative disorders. One of the most predominant biomarkers in neuroimaging is represented by brain age, which has been shown to be
Externí odkaz:
http://arxiv.org/abs/2408.07079
Traditional staining normalization approaches, e.g. Macenko, typically rely on the choice of a single representative reference image, which may not adequately account for the diverse staining patterns of datasets collected in practical scenarios. In
Externí odkaz:
http://arxiv.org/abs/2406.02077
Autor:
Denker, Alexander, Vargas, Francisco, Padhy, Shreyas, Didi, Kieran, Mathis, Simon, Dutordoir, Vincent, Barbano, Riccardo, Mathieu, Emile, Komorowska, Urszula Julia, Lio, Pietro
Generative modelling paradigms based on denoising diffusion processes have emerged as a leading candidate for conditional sampling in inverse problems. In many real-world applications, we often have access to large, expensively trained unconditional
Externí odkaz:
http://arxiv.org/abs/2406.01781
Autor:
Patrício, Cristiano, Barbano, Carlo Alberto, Fiandrotti, Attilio, Renzulli, Riccardo, Grangetto, Marco, Teixeira, Luis F., Neves, João C.
Contrastive Analysis (CA) regards the problem of identifying patterns in images that allow distinguishing between a background (BG) dataset (i.e. healthy subjects) and a target (TG) dataset (i.e. unhealthy subjects). Recent works on this topic rely o
Externí odkaz:
http://arxiv.org/abs/2406.00772
Autor:
Barbano, Carlo Alberto, Renzulli, Riccardo, Grosso, Marco, Basile, Domenico, Busso, Marco, Grangetto, Marco
In this paper, we present the major results from the Covid Radiographic imaging System based on AI (Co.R.S.A.) project, which took place in Italy. This project aims to develop a state-of-the-art AI-based system for diagnosing Covid-19 pneumonia from
Externí odkaz:
http://arxiv.org/abs/2405.11598
Autor:
Gallone, Guglielmo, Iodice, Francesco, Presta, Alberto, Tore, Davide, de Filippo, Ovidio, Visciano, Michele, Barbano, Carlo Alberto, Serafini, Alessandro, Gorrini, Paola, Bruno, Alessandro, Marra, Walter Grosso, Hughes, James, Iannaccone, Mario, Fonio, Paolo, Fiandrotti, Attilio, Depaoli, Alessandro, Grangetto, Marco, de Ferrari, Gaetano Maria, D'Ascenzo, Fabrizio
Aims. To develop a deep-learning based system for recognition of subclinical atherosclerosis on a plain frontal chest x-ray. Methods and Results. A deep-learning algorithm to predict coronary artery calcium (CAC) score (the AI-CAC model) was develope
Externí odkaz:
http://arxiv.org/abs/2403.18756
Autor:
de Clairfontaine, Gaëtan Fichet, Buson, Sara, Pfeiffer, Leonard, Marchesi, Stefano, Azzollini, Alessandra, Baghmanyan, Vardan, Tramacere, Andrea, Barbano, Eleonora, Oswald, Lenz
Recent observations are shedding light on the important role that active galactic nuclei (AGN) play in the production of high-energy neutrinos. In this study, we focus on one object, 5BZB J0630-2406, which is among the blazars recently proposed as as
Externí odkaz:
http://arxiv.org/abs/2310.03698