Lightweight single image super-resolution with attentive residual refinement network

Jinghui Qin; Rumin Zhang

doi:10.1016/j.neucom.2022.05.066

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Lightweight single image super-resolution with attentive residual refinement network

Jinghui Qin Rumin Zhang

Year: 2022 Journal: Neurocomputing Vol: 500 Pages: 846-855 Publisher: Elsevier BV

DOI: 10.1016/j.neucom.2022.05.066

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Keywords:

Residual Computer science Convolutional neural network Upsampling Artificial intelligence Pattern recognition (psychology) Deep learning Block (permutation group theory) Feature (linguistics) Image (mathematics) Algorithm Mathematics

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Advanced Image Processing Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Vision and Imaging

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Image Processing Techniques and Applications

Physical Sciences → Engineering → Media Technology

Lightweight single image super-resolution with attentive residual refinement network

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