Deep learning is transforming most areas of science and technology, including electron
microscopy. This review paper offers a practical perspective aimed at developers with …

Image fusion is a well-recognized and a conventional field of image processing. Image
fusion provides an efficient way of enhancing and combining pixel-level data resulting in …

At the crossing of the statistical and functional analysis, there exists a relentless quest for an
efficient image denoising algorithm. In terms of greyscale imaging, a plethora of denoising …

Single-cell RNA sequencing (scRNA-seq) has enabled researchers to study gene
expression at a cellular resolution. However, noise due to amplification and dropout may …

Sparse representation has attracted much attention from researchers in fields of signal
processing, image processing, computer vision, and pattern recognition. Sparse …

Regular machine learning and data mining techniques study the training data for future
inferences under a major assumption that the future data are within the same feature space …

Social learning in particle swarm optimization (PSO) helps collective efficiency, whereas
individual reproduction in genetic algorithm (GA) facilitates global effectiveness. This …

Most modern commodity imaging systems we use directly for photography—or indirectly rely
on for downstream applications—employ optical systems of multiple lenses that must …

In this paper, we propose a new unsupervised spectral feature selection model by
embedding a graph regularizer into the framework of joint sparse regression for preserving …

Conventional pipelines for capturing, displaying, and storing images are usually defined as
a series of cascaded modules, each responsible for addressing a particular problem. While …