Single Image Super Resolution via Multi-Attention Fusion Recurrent Network

Single Image Super Resolution via Multi-Attention Fusion Recurrent Network

Deep convolutional neural networks have significantly enhanced the performance of single image super-resolution in recent years. However, the majority of the proposed networks are single-channel, making it challenging to fully exploit the advantages of neural networks in feature extraction. This pap...

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Bibliographic Details
Main Authors: Qiqi Kou, Deqiang Cheng, Haoxiang Zhang, Jingjing Liu, Xin Guo, He Jiang
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Super resolution
multiplexing-based
attention fusion mechanism
recurrent network
Online Access:https://ieeexplore.ieee.org/document/10247056/

Internet

https://ieeexplore.ieee.org/document/10247056/

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