A deep learning technique to enhance 3D images of the complex-valued permittivity of the
breast obtained via microwave imaging is investigated. The developed technique is an …

We propose a label enhanced and patch based deep learning phase retrieval approach
which can achieve fast and accurate phase retrieval using only several fringe patterns as …

Single-molecule localization super-resolution microscopy (SMLM) techniques like STORM
and PALM have transformed cellular microscopy by substantially increasing spatial …

This article focuses on the trends, opportunities, and challenges of novel arithmetic for deep
neural network (DNN) signal processing, with particular reference to assisted-and …

Quantitative phase imaging (QPI) is an emerging label-free technique that produces images
containing morphological and dynamical information without contrast agents. Unfortunately …

We present a machine learning-based method for tomographic reconstruction of dense
layered objects, with range of projection angles limited to±10○. Whereas previous …

The space-time reconstruction of sea surface dynamics from satellite observations is a
challenging inverse problem due to the associated irregular sampling. Satellite altimetry …

The exciting advancements that we are currently witnessing in terms of novel materials and
synthesis approaches are leading to the development of colloidal nanoparticles (NPs) with …

Single-image super-resolution (SISR) techniques attempt to reconstruct the finer resolution
version of a given image from its coarser version. In the SISR of hyperspectral data sets, the …

In recent years, there have been significant advances in the use of deep learning methods in
inverse problems such as denoising, compressive sensing, inpainting, and super-resolution …