Danilo Costarelli

J. Comput. Appl. Math., 2024

2023

Approximation error for neural network operators by an averaged modulus of smoothness.

[BibT_eX]

[DOI]

J. Approx. Theory, October, 2023

Preface: Special issue on approximation by linear and nonlinear operators with applications. Part III.

[BibT_eX]

[DOI]

Aleksandra Maria Osowska-Kurczab

Math. Found. Comput., 2023

Improvement of renal image recognition through resolution enhancement.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2023

2022

Density Results by Deep Neural Network operators with Integer weights.

[BibT_eX]

[DOI]

Math. Model. Anal., 2022

Preface: Special issue on approximation by linear and nonlinear operators with applications. Part Ⅱ.

[BibT_eX]

[DOI]

Math. Found. Comput., 2022

Improvement of retinal OCT angiograms by Sampling Kantorovich algorithm in the assessment of retinal and choroidal perfusion.

[BibT_eX]

[DOI]

Appl. Math. Comput., 2022

2021

Enhancement of Cone-Beam Computed Tomography Dental-Maxillofacial Images by Sampling Kantorovich Algorithm.

[BibT_eX]

[DOI]

Symmetry, 2021

Preface: Special issue on approximation by linear and nonlinear operators with applications. Part I.

[BibT_eX]

[DOI]

Math. Found. Comput., 2021

2020

Asymptotic expansions and Voronovskaja type theorems for the multivariate neural network operators.

[BibT_eX]

[DOI]

Math. Found. Comput., 2020

A comparison between the sampling Kantorovich algorithm for digital image processing with some interpolation and quasi-interpolation methods.

[BibT_eX]

[DOI]

Marco Seracini

Appl. Math. Comput., 2020

2019

Convergence in Orlicz spaces by means of the multivariate max-product neural network operators of the Kantorovich type and applications.

[BibT_eX]

[DOI]

Anna Rita Sambucini

Neural Comput. Appl., 2019

Inverse results of approximation and the saturation order for the sampling Kantorovich series.

[BibT_eX]

[DOI]

J. Approx. Theory, 2019

Approximate solutions of Volterra integral equations by an interpolation method based on ramp functions.

[BibT_eX]

[DOI]

Comput. Appl. Math., 2019

Quasi-projection operators with applications to differential-difference expansions.

[BibT_eX]

[DOI]

Aleksandr V. Krivoshein

Maria Skopina

Appl. Math. Comput., 2019

The max-product generalized sampling operators: convergence and quantitative estimates.

[BibT_eX]

[DOI]

Appl. Math. Comput., 2019

2018

Detection of thermal bridges from thermographic images by means of image processing approximation algorithms.

[BibT_eX]

[DOI]

Appl. Math. Comput., 2018

Approximation Problems for Digital Image Processing and Applications.

[BibT_eX]

[DOI]

Marco Seracini

Proceedings of the Computational Science and Its Applications - ICCSA 2018, 2018

2016

Pointwise and uniform approximation by multivariate neural network operators of the max-product type.

[BibT_eX]

[DOI]

Neural Networks, 2016

Max-product neural network and quasi-interpolation operators activated by sigmoidal functions.

[BibT_eX]

[DOI]

J. Approx. Theory, 2016

2015

Neural network operators: Constructive interpolation of multivariate functions.

[BibT_eX]

[DOI]

Neural Networks, 2015

2014

Convergence of a family of neural network operators of the Kantorovich type.

[BibT_eX]

[DOI]

J. Approx. Theory, 2014

Applications of sampling Kantorovich operators to thermographic images for seismic engineering.

[BibT_eX]

[DOI]

CoRR, 2014

2013

Approximation results for neural network operators activated by sigmoidal functions.

[BibT_eX]

[DOI]

Neural Networks, 2013

Multivariate neural network operators with sigmoidal activation functions.

[BibT_eX]

[DOI]

Neural Networks, 2013

Asymptotic-numerical solution of nonlinear systems of one-dimensional balance laws.

[BibT_eX]

[DOI]

Matteo Laurenzi