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pro vyhledávání: '"LANZA, Alessandro"'
We consider an unsupervised bilevel optimization strategy for learning regularization parameters in the context of imaging inverse problems in the presence of additive white Gaussian noise. Compared to supervised and semi-supervised metrics relying e
Externí odkaz:
http://arxiv.org/abs/2403.07026
We propose a novel automatic parameter selection strategy for variational imaging problems under Poisson noise corruption. The selection of a suitable regularization parameter, whose value is crucial in order to achieve high quality reconstructions,
Externí odkaz:
http://arxiv.org/abs/2207.10481
We propose an automatic parameter selection strategy for the problem of image super-resolution for images corrupted by blur and additive white Gaussian noise with unknown standard deviation. The proposed approach exploits the structure of both the do
Externí odkaz:
http://arxiv.org/abs/2108.13091
Autor:
Bortoli Marco, Balasso Antonella, Carta Giovanni, Cestaro Maristella, Colla Viviana, De Togni Alessandra, Gallani Giulio, Giacometti Cristina, Gianni Laura, Giuffreda Lucia, Granella Manuela, Iarabek Marina, Lion Enrico, Mazzi Giuseppe, Migale Caterina, Milan Stefano, Molesini Paola, Moretto Mara, Predonzan Roberta, Priolisi Ornella, Romualdi Rosella, Rubini Cristina, Scarfì Sandra, Tobaldini Elena, Dalla Tiezza Marco, Nale Enrico, Bellanda Massimo, Kennedy Gordon, Sella Gianpietro, Lanza Alessandro, Orian Laura
Publikováno v:
Chemistry Teacher International, Vol 5, Iss 4, Pp 471-480 (2023)
Chemical Quest is an innovative trivia game based on the 102 elements of the periodic table from H to No, developed collaboratively by upper secondary school and university teachers with the aim of increasing the interest of young students (age 14–
Externí odkaz:
https://doaj.org/article/f2f16afa85914da9b8c9e17001973a7b
Over the last 30 years a plethora of variational regularisation models for image reconstruction has been proposed and thoroughly inspected by the applied mathematics community. Among them, the pioneering prototype often taught and learned in basic co
Externí odkaz:
http://arxiv.org/abs/2104.03650
We propose an automatic parameter selection strategy for variational image super-resolution of blurred and down-sampled images corrupted by additive white Gaussian noise (AWGN) with unknown standard deviation. By exploiting particular properties of t
Externí odkaz:
http://arxiv.org/abs/2104.01001
Akademický článek
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In this paper we present a new regularization term for variational image restoration which can be regarded as a space-variant anisotropic extension of the classical isotropic Total Variation (TV) regularizer. The proposed regularizer comes from the s
Externí odkaz:
http://arxiv.org/abs/1908.00801
Publikováno v:
Conference: European Congress on Computational Methods in Applied Sciences and Engineering, 2018
We propose two new variational models aimed to outperform the popular total variation (TV) model for image restoration with L$_2$ and L$_1$ fidelity terms. In particular, we introduce a space-variant generalization of the TV regularizer, referred to
Externí odkaz:
http://arxiv.org/abs/1906.11827