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...

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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

Internet

https://www.mdpi.com/2079-9292/10/17/2072

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