Internet-enabled smartphones and ultra-wide displays are transforming a variety of visual
apps spanning from on-demand movies and 360° videos to video-conferencing and live …

In recent years, convolutional networks have demonstrated unprecedented performance in
the image restoration task of super-resolution (SR). SR entails the upscaling of a single low …

In this article, we propose an energy-efficient convolutional neural network (CNN) based
super-resolution (SR) processor, super-resolution neural processing unit (SRNPU), for …

Recently, convolutional neural networks (CNNs) have actively been applied to computer
vision applications such as style transfer that changes the style of a content image into that …

In this paper, we propose a hardware-efficient residual recurrent neural network for real-time
video super-resolution (VSR) based on field programmable gate array (FPGA). Although …

With the rapid development of computer vision theory and visual display devices, High
Frame Rate (HFR) and Ultra High Definition (UHD) techniques have received increasing …

Super-resolution (SR) techniques aim to restore a high-resolution (HR) image from low-
resolution (LR) images, which are often used to assist the enhancement of image/video …

Super-resolution (SR) based on deep learning has obtained superior performance in image
reconstruction. Recently, various algorithm efforts have been committed to improving image …

In the digital era, the prevalence of low-quality images contrasts with the widespread use of
high-definition displays, primarily due to low-resolution cameras and compression …

The implementation of deep convolutional neural networks (CNN) in single image super-
resolution (SISR) has been successful at improving restoration quality. However, due to …