EdgeFormer: Edge-Aware Efficient Transformer for Image Super-Resolution-Reference-Cited by-同舟云学术

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EdgeFormer: Edge-Aware Efficient Transformer for Image Super-Resolution

Published:2024 Issue: Volume:73 Page:1-12
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Luo Xiaotong¹^ORCID,Ai Zekun¹^ORCID,Liang Qiuyuan¹^ORCID,Xie Yuan²^ORCID,Shi Zhongchao³^ORCID,Fan Jianping³^ORCID,Qu Yanyun¹^ORCID

Affiliation:

1. School of Informatics, Xiamen University, Xiamen, China

2. School of Computer Science and Technology, East China Normal University, Shanghai, China

3. Lenovo Research, Beijing, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Chongqing Municipality

China Computer Federation (CCF) Lenovo Blue Ocean Research Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/19/10367905/10623619.pdf?arnumber=10623619

Reference52 articles.

1. Texture-Enhanced Light Field Super-Resolution With Spatio-Angular Decomposition Kernels

2. Axial Super-Resolution Ultrasound Imaging With Quasi-Monopolar Pulses From a Dual-Frequency Transducer

3. Evanescent microwaves: a novel super-resolution noncontact nondestructive imaging technique for biological applications

4. A Dual Transformer Super-Resolution Network for Improving the Definition of Vibration Image

5. Multiframe Super-Resolution With Dual Pyramid Multiattention Network for Droplet Measurement

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