Image super-resolution using supervised multi-scale feature extraction network

Multim. Tools Appl., pp. 1995-2008, 2020.

Cited by: 0|Bibtex|Views6|DOI:https://doi.org/10.1007/s11042-020-09488-z
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Other Links: academic.microsoft.com|dblp.uni-trier.de

Abstract:

Image super-resolution using deep convolutional networks have recently achieved great successes. However, previous studies have failed to consider the spatial information by simply using a single-size filter, and they do not take full advantage of hierarchical features from low-resolution images, thereby these results are unsatisfactory. ...More

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