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pro vyhledávání: '"Viola, Marco"'
Two-region image segmentation is the process of dividing an image into two regions of interest, i.e., the foreground and the background. To this aim, Chan et al. [Chan, Esedo\=glu, Nikolova, SIAM Journal on Applied Mathematics 66(5), 1632-1648, 2006]
Externí odkaz:
http://arxiv.org/abs/2203.03513
We are interested in the restoration of noisy and blurry images where the texture mainly follows a single direction (i.e., directional images). Problems of this type arise, for example, in microscopy or computed tomography for carbon or glass fibres.
Externí odkaz:
http://arxiv.org/abs/2105.00106
TGV-based restoration of Poissonian images with automatic estimation of the regularization parameter
The problem of restoring images corrupted by Poisson noise is common in many application fields and, because of its intrinsic ill posedness, it requires regularization techniques for its solution. The effectiveness of such techniques depends on the v
Externí odkaz:
http://arxiv.org/abs/2104.14452
Autor:
De Simone, Valentina, di Serafino, Daniela, Gondzio, Jacek, Pougkakiotis, Spyridon, Viola, Marco
Large-scale optimization problems that seek sparse solutions have become ubiquitous. They are routinely solved with various specialized first-order methods. Although such methods are often fast, they usually struggle with not-so-well conditioned prob
Externí odkaz:
http://arxiv.org/abs/2102.13608
We develop a line-search second-order algorithmic framework for minimizing finite sums. We do not make any convexity assumptions, but require the terms of the sum to be continuously differentiable and have Lipschitz-continuous gradients. The methods
Externí odkaz:
http://arxiv.org/abs/2007.15966
The renewed interest in Steepest Descent (SD) methods following the work of Barzilai and Borwein [IMA Journal of Numerical Analysis, 8 (1988)] has driven us to consider a globalization strategy based on SD, which is applicable to any line-search meth
Externí odkaz:
http://arxiv.org/abs/2004.00968
A subspace-accelerated split Bregman method for sparse data recovery with joint l1-type regularizers
We propose a subspace-accelerated Bregman method for the linearly constrained minimization of functions of the form $f(\mathbf{u})+\tau_1 \|\mathbf{u}\|_1 + \tau_2 \|D\,\mathbf{u}\|_1$, where $f$ is a smooth convex function and $D$ represents a linea
Externí odkaz:
http://arxiv.org/abs/1912.06805
Autor:
Wang, Ju1 (AUTHOR) ju.wang@uniroma1.it, Viola, Marco1 (AUTHOR) m.viola@uniroma1.it, Migliorini, Claudia1 (AUTHOR) claudia.migliorini@uniroma1.it, Paoletti, Luca1 (AUTHOR) luca.paoletti@uniroma1.it, Arpicco, Silvia2 (AUTHOR) silvia.arpicco@unito.it, Di Meo, Chiara1 (AUTHOR) chiara.dimeo@uniroma1.it, Matricardi, Pietro1 (AUTHOR) pietro.matricardi@uniroma1.it
Publikováno v:
Pharmaceutics. Oct2023, Vol. 15 Issue 10, p2508. 22p.
Publikováno v:
In European Polymer Journal 7 February 2023 184
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