A<sub>2</sub>M: An Amplification-Arbitrary Module for Remote Sensing Image Super-Resolution-Reference-Cited by-同舟云学术

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A₂M: An Amplification-Arbitrary Module for Remote Sensing Image Super-Resolution

Published:2023 Issue: Volume:20 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Xue Yuan¹^ORCID,Wang Zheyuan²^ORCID,Li Liangliang³^ORCID,Ma Hongbing³

Affiliation:

1. College of Information Science and Engineering, Xinjiang University, Ürümqi, China

2. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China

3. Department of Electronic Engineering, Tsinghua University, Beijing, China

Funder

Shanghai Aerospace Science and Technology Innovation Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

http://xplorestaging.ieee.org/ielx7/8859/10034981/10155436.pdf?arnumber=10155436

Reference24 articles.

1. Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network

2. Embedded Block Residual Network: A Recursive Restoration Model for Single-Image Super-Resolution

3. Image Super-Resolution Using Deep Convolutional Networks

4. A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics

5. Super-Resolution of Single Remote Sensing Image Based on Residual Dense Backprojection Networks

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