RSM combines innovative optical components for super-resolution microscopy, enhancing imaging capabilities and supporting ...

This application note demonstrates how an ammonium bicarbonate-based approach eliminates bottlenecks while maintaining ...

Deconvolution-based speech dereverberation continues to present challenges due to the difficulties in accurately acquiring Room Impulse Responses (RIRs) and the inherently ill-conditioned nature of ...

This repository is a reproducibility study of Network Deconvolution; the original work proposed by Ye et al. (2020). This reproducibility study is conducted to evaluate the ability to reproduce the ...

Purpose: The study aimed to (1) assess the feasibility constrained spherical deconvolution (CSD) tractography to reconstruct crossing fiber bundles with unsedated neonatal diffusion MRI (dMRI), and (2 ...

This study makes a valuable contribution to spatial transcriptomics by rigorously benchmarking cell-type deconvolution methods, assessing their performance across diverse datasets with a focus on ...

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 ...

Position-Dependent Richardson-Lucy deconvolution. Contribute to yusuke1999/PDRL-deconvolution development by creating an account on GitHub.

In this article, LECO recounts a success story around deliberate deconvolution, when a laboratory requires the assistance of state-of-the-art equipment.

For many sensing modalities such as sonar, received signals are corrupted by multipath and can be challenging for automatic classification systems. An approach to jointly deconvolve and classify such ...

The Euler deconvolution satisfactorily estimates the depth of the Benslimane gossan and shows an excellent correlation between the Tilt derivative (TDR) and the HDR_tilt results. Edge detection ...