Recognizing direct relationships between variables connected in a network is a pervasive problem in biological, social and information sciences as correlation-based networks contain numerous indirect ...

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 ...

What will you learn on this course? This course teaches you the theory of deconvolution, how to use and optimise it to find co-eluting peaks and peaks below the baseline in your GC-MS data, through ...

Deconvolution is an image processing method in astrophotography designed to reverse blurring effects, such as those caused by atmospheric conditions and optical imperfections, by mathematically ...

This paper develops nonparametric deconvolution density estimation over SO(N), the group of N × N orthogonal matrices of determinant 1. The methodology is to use the group and manifold structures to ...

The retrospective identification of the drug targets that underlie an observed phenotypic response is termed target deconvolution. Target deconvolution can be achieved by numerous methods including; ...

A new publication from Opto-Electronic Advances, 10.29026/oes.2024.230020 discusses revolutionizing OCT imaging. Deconvolution, an essential method widely employed in various optical imaging ...

Deconvolution is a computational technique of increasing the resolution and SNR (signal to noise ratio) of images captured on an imaging system. Its use existed before the extensive use of confocal ...