A deep recursive multi-scale feature fusion network for image super-resolution

Feiqiang Liu; Xiaomin Yang; Bernard De Baets

doi:10.1016/j.jvcir.2022.103730

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A deep recursive multi-scale feature fusion network for image super-resolution

Feiqiang Liu Xiaomin Yang Bernard De Baets

Year: 2022 Journal: Journal of Visual Communication and Image Representation Vol: 90 Pages: 103730-103730 Publisher: Elsevier BV

DOI: 10.1016/j.jvcir.2022.103730

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Keywords:

Feature (linguistics) Benchmark (surveying) Computer science Block (permutation group theory) Pattern recognition (psychology) Convolutional neural network Scale (ratio) Artificial intelligence Image (mathematics) Layer (electronics) Recursion (computer science) Fusion Algorithm Mathematics

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Advanced Image Processing Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Image Processing Techniques and Applications

Physical Sciences → Engineering → Media Technology

Advanced Vision and Imaging

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

A deep recursive multi-scale feature fusion network for image super-resolution

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