Evaluating the Generalization Ability of Super-Resolution Networks-Reference-Cited by-同舟云学术

Evaluating the Generalization Ability of Super-Resolution Networks

Author:

Liu Yihao¹^ORCID,Zhao Hengyuan²^ORCID,Gu Jinjin³^ORCID,Qiao Yu¹^ORCID,Dong Chao⁴^ORCID

Affiliation:

1. Shanghai Artificial Intelligence Laboratory, Shanghai, China

2. National University of Singapore, Singapore

3. The University of Sydney, Camperdown, NSW, Australia

4. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Joint Lab of CAS-HK

Youth Innovation Promotion Association of the Chinese Academy of Sciences

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software

Link

Reference48 articles.

1. Reflash dropout in image super-resolution;kong,2021

5. On large-batch training for deep learning: Generalization gap and sharp minima;keskar,2016

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