Abstract: Recently, studies have shown the potential of integrating field-type iterative methods with deep learning (DL) techniques in solving inverse scattering problems (ISPs). In this article, we ...
Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have ...
Abstract: In this study, we investigate an extended class of hierarchical variational inequalities (SEGHVIDs, i.e., generalized hierarchical variational inequalities with differentiable operators, ...
Using a Deep Residual Convolutional Neural Network as an Image Transformation Network (ITN). We train the ITN to transform input images into output images. We use a VGG19 which is pre-trained on ...
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Riemannian Geometry-Based Spatial Filtering (RSF) is a method based on Riemannian geometry designed to improve the accuracy of motor imagery (MI) and electroencephalogram (EEG) signal classification.