This paper treats the inverse denoising problem which aims to compute simultaneously the
clean image and the weighting parameter λ. The formulated denoising problem is posed …

In this work, we introduce an efficient second-order reaction–diffusion (RD) equation for
noise removal and image super-resolution. The main idea is to decompose the image into …

Aiming at the problem of Transformers lack of local spatial receptive field and discontinuous
boundary loss in rotating object detection, in this paper, we propose a Transformer-based …

In this paper, we propose an improved version of Twin SVM using a non-smooth
optimization method. Twin SVM generally consists in determining two non-parallel planes by …

Data completion known as Cauchy problem is one most investigated inverse problems. In
this work we consider a Cauchy problem associated with Helmholtz equation. Our …

This paper deals with the machine learning model as a framework of regularized loss
minimization problem in order to obtain a generalized model. Recently, some studies have …

This work deals with the study of ill-posed inverse problems involved in many signal
processing areas and image analysis. Indeed, the image degradation during the data …

This paper deals with an inverse Cauchy problem governed by an elliptical equation defined
in non-homogeneous domain. We propose two approaches based on alternating algorithm …

This work elaborated an improved method to multiframe super-resolution (SR), which
involves a nonlocal first-order regularization combined with a nonlocal p-Laplacian term …

This research introduces an enhanced approach for multiframe super-resolution (SR) that
incorporates a bilevel optimization technique for learning the space variable weights …