Iterative dual regression network for blind image super-resolution
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Signal Processing
Link
https://link.springer.com/content/pdf/10.1007/s11760-022-02460-4.pdf
Reference37 articles.
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2. Chen, L., Tang, R., Anisetti, M., Yang, X.: A lightweight iterative error reconstruction network for infrared image super-resolution in smart grid. Sustain. Cities Soc. 66, 102520 (2021)
3. Chen, L., Yang, X., Jeon, G., Anisetti, M., Liu, K.: A trusted medical image super-resolution method based on feedback adaptive weighted dense network. Artif. Intell. Med. 106, 101857 (2020)
4. Dong, C., Loy, C. C., He, K., Tang, X.: Learning a deep convolutional network for image super-resolution. In: European Conference on Computer Vision, pp. 184–199. Springer (2014)
5. Dong, C., Loy, C. C., Tang, X.: Accelerating the super-resolution convolutional neural network. In: European Conference on Computer Vision, pp. 391–407. Springer (2016)
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