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Transfer Learning Based on A+ for Image Super-Resolution
[chapter]
2016
Lecture Notes in Computer Science
Example learning-based super-resolution (SR) methods are effective to generate a high-resolution (HR) image from a single low-resolution (LR) input. And these SR methods have shown a great potential for many practical applications. Unfortunately, most of popular example learning-based approaches extract features from limited training images. These training images are insufficient for super resolution task. Our work is to transfer some supplemental information from other domains. Therefore, in
doi:10.1007/978-3-319-47650-6_26
fatcat:pnmziyjymvan5dm7dabisvdasm