In several supervised learning applications, it happens that reconstruction methods have to be applied repeatedly before being able to achieve the final solution. Marco Di Prato (184554164)'s profile on Myspace, the place where people come to connect, discover, and share. This article presents preliminary results on NACO/VLT images of close binary stars ob- tained by means of a Richardson-Lucy-based algorithm of super-resolution, where down to roughly a half-resolution element is attained, and with confirmation from VLTI observations in one of the cases treated. Join ResearchGate to find the people and research you need to help your work. A few methods have been proposed for dealing with this problem and their performance is not always satisfactory. [1] S. Bonettini, I. Loris, F. Porta, M. Prato, Variable metric inexact line-search based methods for nonsmooth optimization, SIAM Journal on Optimization 26 (2016), 891-921 I genitori di Luca, Silvana e Giuseppe, sono distrutti dal dolore e chiedono giustizia per il loro unico figlio, ucciso in un modo così brutale. 3 anni fa . Dipartimento di Scienze Fisiche, Informatiche e Matematiche, Università di Modena e Reggio Emilia - Cited by 1,013 - Inverse problems - image processing - machine learning This was an... X-radiation from energetic electrons is the prime diagnostic of The aim of this paper is to present the convergence analysis of a very general class of gradient projection methods for smooth, constrained, possibly nonconvex, optimization. The scaled gradient projection (SGP) method is a first-order optimization method applicable to the constrained minimization of smooth functions and exploiting a scaling matrix multiplying the gradient and a variable steplength parameter to improve the convergence of the scheme. Examples of metrics which are included in our framework are the Euclidean distance, the scaled Euclidean distance, where the scaling matrix is given by strategies such as the Majorization-Minimization or the Split Gradient techniques, and Bregman distances. Il testamento di Marco Prato è stato scritto prima della lettera trovata in cella accanto al suo corpo esamine. function. In this paper we propose a blind deconvolution method which applies to data This paper deals with a general framework for inexact forward--backward algorithms aimed at minimizing the sum of an analytic function and a lower semicontinuous, subanalytic, convex term. In this paper we address the problem of estimating the phase from color images acquired with differential-interference-contrast microscopy. He received the M.Sc. In these situations, the availability of learning algorithms able to provide effective predictors in a very short time may lead to remarkable improvements in the overall computational req... We describe recently proposed algorithms, denoted scaled gradient Emilie Chouzenoux 12 publications . Il «testamento» di Marco Prato è stato scritto per tempo, ancor prima della lettera trovata in cella accanto al suo corpo la notte tra lunedì e martedì. perturbed by Poisson noise. reconstruction of the solution, involving choices of adaptive parameters Blind deconvolution is the problem of image deblurring when both the original object and the blur are unknown. Due to our privacy policy, only current members can send messages to people on ResearchGate. Il «testamento» di Marco Prato è stato scritto per tempo, ancor prima della lettera trovata in cella accanto al suo corpo la notte tra lunedì e martedì. The cross section for bremsstrahlung photon emission in solar flares is, in general, a function of the angle θ between the incoming electron and the outgoing photon directions. … See the Instructional Videos page for … Visualizza il profilo di Marco Prati su LinkedIn, la più grande comunità professionale al mondo. Genitori - ICS Marco Polo di Prato. both maximum likelihood and Bayesian approaches are considered. The RHESSI spacecraft images hard X-ray emission from solar flares with an angular resolution down to ~2'' and an energy resolution of 1 keV. We propose a method for the construction of electron flux maps at different el... Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) is a nine-collimators satellite detecting X–rays and γ–rays emitted by the Sun during flares. The aim of this work is to present a new and efficient optimization method for the solution of blind deconvolution problems with data corrupted by Gaussian noise, which can be reformulated as a constrained minimization problem whose unknowns are the point spread function (PSF) of the acquisition system and the true image. The method avoids the “traditional” noise-sensitive step of stacking independent images made in different count-based energy intervals. Google has many special features to help you find exactly what you're looking for. Alessandro Chiuso 10 publications . values. He received the, Department of Physics, Informatics and Mathematics, Friedrich-Alexander-University of Erlangen-Nürnberg, Engineering, Applied and Computational Mathematics, Convergence of Inexact Forward--Backward Algorithms Using The Forward--Backward Envelope, New convergence results for the inexact variable metric forward–backward method, A Hybrid Interior Point - Deep Learning Approach for Poisson Image Deblurring, Deep neural networks for inverse problems with pseudodifferential operators: an application to limited-angle tomography, Efficient Block Coordinate Methods for Blind Cauchy Denoising, Recent Advances in Variable Metric First-Order Methods, Multiple Image Deblurring with High Dynamic-Range Poisson Data, Deep Unfolding of a Proximal Interior Point Method for Image Restoration, Learned Image Deblurring by Unfolding a Proximal Interior Point Algorithm, A Bregman inexact linesearch–based forward–backward algorithm for nonsmooth nonconvex optimization, A block coordinate variable metric linesearch based proximal gradient method, A comparison of edge-preserving approaches for differential interference contrast microscopy, On the convergence of a linesearch based proximal-gradient method for nonconvex optimization, TV-regularized phase reconstruction in differential-interference-contrast (DIC) microscopy, On the constrained minimization of smooth Kurdyka—Łojasiewicz functions with the scaled gradient projection method, The software package AIRY 7.0: new efficient deconvolution methods for post-adaptive optics data, On the convergence of variable metric line-search based proximal-gradient method under the Kurdyka-Lojasiewicz inequality, Phase estimation in differential-interference-contrast (DIC) microscopy, New convergence results for the scaled gradient projection method, Application of cyclic block generalized gradient projection methods to poisson blind deconvolution, Variable Metric Inexact Line-Search-Based Methods for Nonsmooth Optimization, A convergent least-squares regularized blind deconvolution approach, A blind deconvolution method for ground based telescopes and Fizeau interferometers, A cyclic block coordinate descent method with generalized gradient projections, An alternating minimization method for blind deconvolution in astronomy, An alternating minimization method for blind deconvolution from Poisson data, Strehl-constrained reconstruction of post-adaptive optics data and the Software Package AIRY, v. 6.1, A New Steplength Selection for Scaled Gradient Methods with Application to Image Deblurring, A new general framework for gradient projection methods, A Scaled Gradient Projection Method for Bayesian Learning in Dynamical Systems, Accelerated gradient methods for the x-ray imaging of solar flares, Point Spread Function extraction in crowded fields using blind deconvolution, Deconvolution-based super resolution for post-AO data, On the filtering effect of iterative regularization algorithms for discrete inverse problems, Filter factor analysis of scaled gradient methods for linear least squares, An image reconstruction method from Fourier data with uncertainties on the spatial frequencies, A New Semiblind Deconvolution Approach for Fourier-Based Image Restoration: An Application in Astronomy, A deconvolution algorithm for imaging problems from Fourier data, A convergent blind deconvolution method for post-adaptive-optics astronomical imaging, A practical use of regularization for supervised learning with kernel methods, Scaled Gradient Projection Methods for Astronomical Imaging, Efficient deconvolution methods for astronomical imaging: Algorithms and IDL-GPU codes, Composition of fine and coarse particles in a coastal site of the central Mediterranean: Carbonaceous species contributions, Accuracy of Funduscopy to Identify True Edema versus Pseudoedema of the Optic Disc, Deducing Electron Properties From Hard X-Ray Observations, A regularization algorithm for decoding perceptual temporal profiles from fMRI data, A Novel Gradient Projection Approach for Fourier-Based Image Restoration, Nonnegative image reconstruction from sparse Fourier data: A new deconvolution algorithm, The Location of Centroids in Photon and Electron Maps of Solar Flares, Hard X-ray Imaging of Solar Flares Using Interpolated Visibilities, Regularization Methods for the Solution of Inverse Problems in Solar X-ray and Imaging Spectroscopy, A Regularized Visibility-Based Approach to Astronomical Imaging Spectroscopy, From BOLD-FMRI signals to the prediction of subjective pain perception through a regularization algorithm, Anisotropic Bremsstrahlung Emission and the Form of Regularized Electron Flux Spectra in Solar Flares, Inverse problems in machine learning: An application to brain activity interpretation, A visibility-based approach using regularization for imaging-spectroscopy in solar X-ray astronomy, Determining the Spatial Variation of Accelerated Electron Spectra in Solar Flares, Imaging spectroscopy of hard x-ray sources in solar flares using regularized analysis of source visibilities, Regularized solution of the solar Bremsstrahlung inverse problem: model dependence and implementation issues, Imaging spectroscopy from visibilities in the RHESSI era, Electron flux maps of solar flares: a regularization approach to RHESSI imaging spectroscopy, Electron Flux Spectral Imaging of Solar Flares through Regularized Analysis of Hard X-Ray Source Visibilities, Electron-Electron Bremsstrahlung Emission and the Inference of Electron Flux Spectra in Solar Flares, Determination of Electron Flux Spectrum Images in Solar Flares using Regularized Analysis of Hard X-Ray Source Visibilities, Regularized Reconstruction of the Differential Emission Measure from Solar Flare Hard X-Ray Spectra, Regularized solution of the solar Bremsstrahlung inverse problem: Model dependence and implementation issues, Construction of Electron Flux Images in Solar Flares using Interpolated Visibilities, Part A Astrophysics, Cosmology and Earth Physics 1, Variable metric line-search based methods for nonconvex optimization, Department of Physical and Chemical Sciences, Department of Biomedical, Metabolical and Neurosciences, Dipartimento di Informatica, Bioingegneria, Robotica e Ingegneria dei Sistemi (DIBRIS), Department of Mathematics and Computer Science, School of Systems Engineering and Informatics, School of Biotechnology and Biomolecular Sciences (BABS).

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