Abstract: The success of modern single image super-resolution (SISR) algorithms is inspired by the development of deep convolutional neural networks (CNNs). However, these CNN-based methods require ...

These parameters are fit using an alternating optimization method, which iteratively converges to the optimal values. An initial registration step additionally ensures that all input images are well ...

1 Department of Computer Science and Engineering, Jahangirnagar University, Dhaka, Bangladesh. 2 Department of Computer Science and Engineering, Green University of Bangladesh, Narayanganj, Bangladesh ...

Low-resolution images (LR) are input, and feature maps are obtained through 3×3 convolution. After passing through a residual in residual (RIR) module, followed by upsampling and a 3×3 convolution ...

This repository contains data and scripts required for reproducing the results presented in the paper Calibration-free single-frame super-resolution fluorescence microscopy by Anežka Dostálová, ...

Nvidia’s RTX series include some of the best graphics cards on the market and are known for two flagship features: real-time ray tracing and Deep Learning Super Sampling (DLSS). While ray tracing is ...

What is Nvidia DLSS? Deep Learning Super Sampling, or DLSS, is a suite of software technologies that use AI to help you boost your frame rate or game image quality. Originally just a technique for ...

Deep learning is progressively emerging as a vital tool for image reconstruction in light field microscopy. The present review provides a comprehensive examination of the latest advancements in light ...

In this study, we propose a CNN-GAN-based real-time processing technique for filtering images of underwater cables used in power systems. This addresses the excessive interference impurities that are ...

Microsoft is bringing its own AI based super resolution technique, dubbed Automatic super resolution (Auto SR), to the masses by baking it right into Windows. Like other solutions from AMD, Intel and ...