Residual Triplet Attention Network for Single-Image Super-Resolution

Residual Triplet Attention Network for Single-Image Super-Resolution

Single-image super-resolution (SISR) techniques have been developed rapidly with the remarkable progress of convolutional neural networks (CNNs). The previous CNNs-based SISR techniques mainly focus on the network design while ignoring the interactions and interdependencies between different dimensi...

Full description

Bibliographic Details
Main Authors: Feng Huang, Zhifeng Wang, Jing Wu, Ying Shen, Liqiong Chen
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Electronics
Subjects:
image super-resolution
attention mechanism
convolutional neural networks
deep learning
Online Access:https://www.mdpi.com/2079-9292/10/17/2072

Similar Items

Similar Items