3 citations · 7 across the 7 of their papers we have counts for
7 papers
Bayesian Inversion via Probabilistic Cellular Automata: an application to image denoising
Danilo Costarelli, Michele Piconi, Alessio Troiani
We propose using Probabilistic Cellular Automata (PCA) to address inverse problems with the Bayesian approach. In particular, we use PCA to sample from an approximation of the post…
A characterization of generalized Lipschitz classes by the rate of convergence of semi-discrete operators
Danilo Costarelli, Michele Piconi, Gianluca Vinti
In this paper, we establish a comprehensive characterization of the generalized Lipschitz classes through the study of the rate of convergence of a family of semi-discrete sampling…
Image resizing by neural network operators and their convergence rate with respect to the -norm and the dissimilarity index defined through the continuous SSIM
Danilo Costarelli, Mariarosaria Natale, Michele Piconi
In literature, several algorithms for imaging based on interpolation or approximation methods are available. The implementation of theoretical processes highlighted the necessity o…
Strong and weak sharp bounds for Neural Network Operators in Sobolev-Orlicz spaces and their quantitative extensions to Orlicz spaces
Danilo Costarelli, Michele Piconi
In this paper, we establish sharp bounds for a family of Kantorovich-type neural network operators within the general frameworks of Sobolev-Orlicz and Orlicz spaces. We establish b…
Microwave Remote Sensing of Soil Moisture, Above Ground Biomass and Freeze-Thaw Dynamic: Modeling and Empirical Approaches
Laura Angeloni, Domenico Daniele Bloisi, Paolo Burghignoli +6
Human actions have accelerated changes in global temperature, precipitation patterns, and other critical Earth systems. Key markers of these changes can be linked to the dynamic of…
Implementation of neural network operators with applications to remote sensing data
Danilo Costarelli, Michele Piconi
In this paper, we provide two algorithms based on the theory of multidimensional neural network (NN) operators activated by hyperbolic tangent sigmoidal functions. Theoretical resu…
On the convergence properties of Durrmeyer-Sampling Type Operators in Orlicz spaces
Danilo Costarelli, Michele Piconi, Gianluca Vinti
Here we provide a unifying treatment of the convergence of a general form of sampling type operators, given by the so-called Durrmeyer sampling type series. In particular we provid…