首页> 外文会议>International Conference on Culture-oriented Science and Technology >A Survey of Super-Resolution Based on Deep Learning
【24h】

A Survey of Super-Resolution Based on Deep Learning

机译:基于深度学习的超分辨率研究

获取原文

摘要

Image super-resolution (SR) is an important low-level visual task in the field of image processing. It is used to enhance the resolution of images or videos and has a wide range of applications. In recent years, many researchers have begun to apply deep learning-based methods to SR task, which can significantly improve the quality of restored images. In this paper, we will introduce the concept of image super-resolution task, several typical CNNs based on supervised SR, unsupervised SR as well as the future research directions of SR.
机译:图像超分辨率(SR)是图像处理领域中重要的低级视觉任务。它用于提高图像或视频的分辨率,并具有广泛的应用范围。近年来,许多研究人员已开始将基于深度学习的方法应用于SR任务,这可以显着提高恢复图像的质量。在本文中,我们将介绍图像超分辨率任务的概念,基于监督SR,无监督SR的几种典型CNN以及SR的未来研究方向。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号