E-LIB Suche - Ergebnisse für: Pragliola, Monica

1

Speckle noise removal via learned variational models:

Cuomo, Salvatore ; De Rosa, Mariapia ; Izzo, Stefano..
Applied Numerical Mathematics. 200 (2024) - p. 162-178 , 2024

Link: https://doi.org/10.1016/..

2

Insights on the different convergences in Extreme Learning ..:

De Falco, Davide Elia ; Calabrò, Francesco ; Pragliola, Monica
Neurocomputing. 599 (2024) - p. 128061 , 2024

Link: https://doi.org/10.1016/..

3

Parameter-free restoration of piecewise smooth images:

Lanza, Alessandro ; Pragliola, Monica ; Sgallari, Fiorella
ETNA - Electronic Transactions on Numerical Analysis. 59 (2023) - p. 202-229 , 2023

Link: https://doi.org/10.1553/..

4

Masked unbiased principles for parameter selection in varia..:

Bevilacqua, Francesca ; Lanza, Alessandro ; Pragliola, Monica.
Inverse Problems. 39 (2023) 3 - p. 034002 , 2023

Link: https://doi.org/10.1088/..

5

Whiteness-based parameter selection for Poisson data in var..:

Bevilacqua, Francesca ; Lanza, Alessandro ; Pragliola, Monica.
Applied Mathematical Modelling. 117 (2023) - p. 197-218 , 2023

Link: https://doi.org/10.1016/..

6

Inducing sparsity via the horseshoe prior in imaging proble..:

Dong, Yiqiu ; Pragliola, Monica
Inverse Problems. 39 (2023) 7 - p. 074001 , 2023

Link: https://doi.org/10.1088/..

7

On and Beyond Total Variation Regularization in Imaging: Th..:

Pragliola, Monica ; Calatroni, Luca ; Lanza, Alessandro.
SIAM Review. 65 (2023) 3 - p. 601-685 , 2023

Link: https://doi.org/10.1137/..

8

ADMM-Based Residual Whiteness Principle for Automatic Param..:

Pragliola, Monica ; Calatroni, Luca ; Lanza, Alessandro.
Journal of Mathematical Imaging and Vision. 65 (2022) 1 - p. 99-123 , 2022

Link: https://doi.org/10.1007/..

9

A comparison of parameter choice rules for $$\ell ^p$$-$$\e..:

Buccini, Alessandro ; Pragliola, Monica ; Reichel, Lothar.
ANNALI DELL'UNIVERSITA' DI FERRARA. 68 (2022) 2 - p. 441-463 , 2022

Link: https://doi.org/10.1007/..

10

Residual Whiteness Principle for Automatic Parameter Select..:

, In: Lecture Notes in Computer Science; Scale Space and Variational Methods in Computer Vision,

Pragliola, Monica ; Calatroni, Luca ; Lanza, Alessandro. - p. 476-488 , 2021

Link: https://doi.org/10.1007/..

11

Nearly Exact Discrepancy Principle for Low-Count Poisson Im..:

Bevilacqua, Francesca ; Lanza, Alessandro ; Pragliola, Monica.
Journal of Imaging. 8 (2021) 1 - p. 1 , 2021

Link: https://doi.org/10.3390/..

12

Sparsity Promoting Hybrid Solvers for Hierarchical Bayesian..:

Calvetti, Daniela ; Pragliola, Monica ; Somersalo, Erkki
SIAM Journal on Scientific Computing. 42 (2020) 6 - p. A3761-A3784 , 2020

Link: https://doi.org/10.1137/..

13

Residual whiteness principle for parameter-free image resto..:

Lanza, Alessandro ; Pragliola, Monica ; Sgallari, Fiorella
ETNA - Electronic Transactions on Numerical Analysis. 53 (2020) - p. 329-351 , 2020

Link: https://doi.org/10.1553/..

14

Adaptive parameter selection for weighted-TV image reconstr..:

Calatroni, Luca ; Lanza, Alessandro ; Pragliola, Monica.
Journal of Physics: Conference Series. 1476 (2020) 1 - p. 012003 , 2020

Link: https://doi.org/10.1088/..

15

Space-Adaptive Anisotropic Bivariate Laplacian Regularizati..:

, In: VipIMAGE 2019; Lecture Notes in Computational Vision and Biomechanics,

Calatroni, Luca ; Lanza, Alessandro ; Pragliola, Monica. - p. 67-76 , 2019

Link: https://doi.org/10.1007/..