Single Image Super Resolution Model Using Learnable Weight Factor in Residual Skip Connection

Single Image Super Resolution Model Using Learnable Weight Factor in Residual Skip Connection

In single image super-resolution problems, the recent feed forward deep learning architectures use residual connections in order to preserve local features and carry them through the next layer. In a simple residual skip connection, all the features of the earlier layer are concatenated with the fea...

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Bibliographic Details
Main Authors: Ruaa A. Al-falluji, Aliaa A. A Youssif, Shawkat K. Guirguis
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Super resolution
image enhancement
image reconstruction
residual skip connection
convolutional neural networks
Online Access:https://ieeexplore.ieee.org/document/8705224/

Internet

https://ieeexplore.ieee.org/document/8705224/

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