Structured Fusion Attention Network for Image Super-Resolution Reconstruction

Structured Fusion Attention Network for Image Super-Resolution Reconstruction

To improve the extraction ability of image features, reduce the complexity of model parameters, and enhance the reconstruction effect of image super-resolution (SR), a structured fusion attention network (SFAN) is proposed. Firstly, the deep convolution method is used to extract shallow features fro...

Full description

Bibliographic Details
Main Authors: Yaonan Dai, Jiuyang Yu, Tianhao Hu, Yang Lu, Xiaotao Zheng
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Image super-resolution
structured residual
fusion attention
low model parameters
SFAN
Online Access:https://ieeexplore.ieee.org/document/9737465/

Internet

https://ieeexplore.ieee.org/document/9737465/

Similar Items