Super-resolution microscopy surpasses the diffraction limit and enables the visualization of biomolecular structures with unprecedented detail. These techniques have been widely used in many ...

Random fluctuations in the intensity and energy of X-ray lasers, which generally limit performance, have been harnessed for high-resolution spectroscopy.

In contrast, our work introduces SuperTac, a novel framework that integrates dimensionality reduction via a Variational Autoencoder with Residual-In-Residual Blocks to achieve real-time ...

Visualizing the spatial organization of biomolecules can advance our understanding of cellular function, yet achieving nanoscale resolution across diverse targets and samples remains challenging. This ...

Aiming at the problems of traditional image super-resolution reconstruction algorithms in the image reconstruction process, such as small receptive field, insufficient multi-scale feature extraction, ...

Automatic Super Resolution (Auto SR) is now officially part of Windows 11, but what does it actually do, and how do you use it?

Overview This project is a Python implementation of an image super-resolution application using an autoencoder neural network built with Keras. It enables users to upscale low-resolution images to ...

AI super resolution improves video and images for satellite imagery, digital cameras, medical and security purposes, entertainment and more.