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分级监督范式指导下的遥感图像超分辨率方法
Translated title of the contribution
:
Remote sensing image super-resolution guided by multi-level supervision paradigm
Mingkai Li,
Qizhi Xu
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Corresponding author for this work
School of Mechatronical Engineering
Beijing Institute of Technology
Research output
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peer-review
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Engineering
Resolution Component
100%
Scale Factor
93%
Tasks
26%
Image Reconstruction
13%
Feature Extraction
13%
Building Block
13%
Posedness
13%
Experimental Result
6%
State-of-the-Art Method
6%
Spatial Resolution
6%
Multiscale
6%
Reconstructed Image
6%
Layer Network
6%
Output Image
6%
Ground Truth Image
6%
Earth and Planetary Sciences
Remote Sensing
100%
Image Reconstruction
66%
Pattern Recognition
66%
State of the Art
33%
Spatial Resolution
33%
Computer Science
super resolution
100%
Remote Sensing Image
100%
Network Structures
11%
Feature Extraction
5%
Image Reconstruction
5%
Resolution Method
5%
Building-Blocks
5%
Experimental Result
2%
Network Layer
2%
Spatial Resolution
2%
Reconstructed Image
2%
Global Feature
2%
Performance Gain
2%
Ground Truth Image
2%
Resolution Process
2%
The Super-Resolution Generative Adversarial Network
2%
Biochemistry, Genetics and Molecular Biology
Remote Sensing
100%
Reconstruction
66%