Multi-scale gated network for efficient image super-resolution-Reference-Cited by-同舟云学术

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Multi-scale gated network for efficient image super-resolution

Published:2024-05-03 Issue: Volume: Page:
ISSN:0178-2789
Container-title:The Visual Computer
language:en
Short-container-title:Vis Comput

Author:

Miao Xuan,Li Shijie,Li Zheng,Xu Wenzheng,Yang Ning

Funder

National Key Research and Development Program of China

Science and Technology Planning Project of Sichuan Province

National Major Project of China

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s00371-024-03410-6.pdf

Reference55 articles.

1. Zhang, S., Liang, G., Pan, S., Zheng, L.: A fast medical image super resolution method based on deep learning network. IEEE Access 7, 12319–12327 (2018)

2. Uiboupin, T., Rasti, P., Anbarjafari, G., Demirel, H.: Facial image super resolution using sparse representation for improving face recognition in surveillance monitoring. In: 2016 24th Signal Processing and Communication Application Conference (SIU), pp. 437–440 (2016)

3. Wang, P., Bayram, B., Sertel, E.: A comprehensive review on deep learning based remote sensing image super-resolution methods. Earth-Sci. Rev. 232, 104110 (2022)

4. Chen, Y., Phonevilay, V., Tao, J., Chen, X., Xia, R., Zhang, Q., Yang, K., Xiong, J., Xie, J.: The face image super-resolution algorithm based on combined representation learning. Multim. Tools Appl. 80, 30839–30861 (2021)

5. Capel, D., Zisserman, A.: Computer vision applied to super resolution. IEEE Signal Process. Mag. 20(3), 75–86 (2003)

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