Methods to deconvolute experimental mixture spectra via a model that is trained on experimental pure-component spectra. This is documentation for https://github.com ...

Abstract: Neural network frameworks today commonly implement Deconvolution and closely related Convolution operator via a combination of GEMM (dense matrix-matrix multiplication) and a memory ...

Abstract: Deconvolution technology, as an effective means to enhance the resolution of seismic data, has emerged as a prominent research area in the field of seismic exploration. However, due to its ...

Jolideco is a Python package for Joint Likelihood Deconvolution of astronomical images affected by Poisson noise. It allows you to deblur and denoise images and do a joint image reconstruction of ...

The Windows version of the Python interpreter can be run from the command line the same way it’s run in other operating systems, by typing python or python3 at the prompt. But there’s a feature unique ...

Tissues are constituted of heterogeneous cell types. Although single-cell RNA sequencing has paved the way to a deeper understanding of organismal cellular composition, the high cost and technical ...

Selecting the right deconvolution method to analyze the composition of complex mixtures of cells just got easier. Researchers derived clear guidelines scientists can use to determine the deconvolution ...

Biomedical scientists are increasingly using deconvolution methods, those used to computationally analyze the composition of complex mixtures of cells. One of their challenges is to select one method ...

Electron tomography is used to reveal the structure of cells in three dimensions (3D). The combination with cryogenic fixation provides a snapshot in time of the living state. However, cryotomography ...