… In this paper, we study the super resolution of images based on … resolution enhancement
of images with subtitles as we know, the method proposed in this study is better than the image …

… image restoration tasks. To solve these problems, we propose a lightweight super-resolution
network called image … in image feature extraction but also adaptively enhancing and fusing …

… resolution and specific depth. In this work, we mitigated these limitations via deep learning
image restoration … low-contrast images into high-speed and high-contrast images, effectively …

… proposed, which enhanced the ability of … (Image Restoration using Swin transformer),
indicates that the proposed network can efficiently reconstruct the textures and details of the image …

… 神經網絡(Capsule Image Restoration Neural Network, CIRNN… In this paper, we present
Capsule Image Restoration Neural … (CNN)-based image super-resolution (SR) frameworks. The …

… image restoration to progressively refine the restored images. … the restoration process provides
incremental enhancements, … In-vivo TFMPM image restoration using a three-stage U-Net …

… reasonable and real images through the confrontation … in the fields of image restoration
and super-resolution generation. … , scene layout enhancement and universality enhancement. …

… Abstract: Image super-resolution is one of the most important branches of image restoration,
… restoring or reconstructing images or videos, thus enhancing the resolution of the original …

… resolution image is got after performing image restoration to above reconstructed high resolution
image. … , which solves the problem of spatial resolution enhancement but MTF reduction …