Random Undersampled Digital Elevation Model Super-Resolution Based on Terrain Feature-Aware Deep Learning Network
The digital elevation model (DEM) provides important data support for geographic information analysis. However, due to the limitation of measurement cost and complex terrain, the collected DEMs often have randomly missing undersampled points and low sampling density. Neural networks have been shown...
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| 主要な著者: | , , , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
IEEE
2025-01-01
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| シリーズ: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| 主題: | |
| オンライン･アクセス: | https://ieeexplore.ieee.org/document/10909506/ |
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