Cryo-electron tomography can uniquely probe the native cellular environment for
macromolecular structures. Tomograms feature complex data with densities of diverse …

Cryo-electron tomography (cryo-ET) plays a critical role in imaging microorganisms in situ in
terms of further analyzing the working mechanisms of viruses and drug exploitation, among …

Clustering models constitute a class of unsupervised machine learning methods which are
used in a number of application pipelines, and play a vital role in modern data science. With …

Advances in cryogenic electron microscopy (cryoEM) single particle analysis have
revolutionized structural biology by facilitating the in vitro determination of atomic-and near …

In this article, an adaptive gradient projection correction (AGPC) method for resistivity array
imaging logging is proposed. Due to the irregular spin and swing of the subsurface resistivity …

Outdoor vision sensing systems often struggle with poor weather conditions, such as snow
and rain, which poses a great challenge to existing video desnowing and deraining …

3D subtomogram image alignment, clustering, and segmentation are vital to
macromolecular structure recognition in cryo-electron tomography (cryo-ET). However …

Recent biotechnological developments in cryo-electron tomography allow direct
visualization of native sub-cellular structures with unprecedented details and provide …

In this paper, we propose a new clustering module that can be trained jointly with existing
neural network layers. Specifically, we have designed a generic clustering module with a …

Let x and x be single dimensional real valued random variables. These random variables
are iid transformed by transforming x (og) by randomly drawn transformations from K …