Single Image Super-Resolution Using Dual-Branch Convolutional Neural Network

Single Image Super-Resolution Using Dual-Branch Convolutional Neural Network

Recent advances in convolutional neural networks have demonstrated impressive reconstruction for single image super-resolution (SR). However, most of the existing methods are to achieve better performance by directly stacking more convolution layers in a chain way. As the depth increases, it not onl...

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Bibliographic Details
Main Authors: Xiaodong Gao, Ling Zhang, Xianglin Mou
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Convolutional neural network
single image super-resolution
dilated convolution
deconvolution
skip connection
Online Access:https://ieeexplore.ieee.org/document/8588998/

Internet

https://ieeexplore.ieee.org/document/8588998/

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