[HTML][HTML] A global-information-constrained deep learning network for digital elevation model super-resolution
X Han, X Ma, H Li, Z Chen - Remote Sensing, 2023 - mdpi.com
High-resolution DEMs can provide accurate geographic information and can be widely used
in hydrological analysis, path planning, and urban design. As the main complementary …
in hydrological analysis, path planning, and urban design. As the main complementary …
Feature-enhanced deep learning network for digital elevation model super-resolution
X Ma, H Li, Z Chen - IEEE Journal of Selected Topics in …, 2023 - ieeexplore.ieee.org
The high-resolution digital elevation model (HR DEM) plays an important role in
hydrological analysis, cartographic generalization, and national security. As the main high …
hydrological analysis, cartographic generalization, and national security. As the main high …
Terrain feature-aware deep learning network for digital elevation model superresolution
Neural networks (NNs) have demonstrated the potential to recover finer textural details from
lower-resolution images by superresolution (SR). Given similar grid-based data structures …
lower-resolution images by superresolution (SR). Given similar grid-based data structures …
[HTML][HTML] An enhanced residual feature fusion network integrated with a terrain weight module for digital elevation model super-resolution
G Chen, Y Chen, JP Wilson, A Zhou, Y Chen, H Su - Remote Sensing, 2023 - mdpi.com
The scale of digital elevation models (DEMs) is vital for terrain analysis, surface simulation,
and other geographic applications. Compared to traditional super-resolution (SR) methods …
and other geographic applications. Compared to traditional super-resolution (SR) methods …
Deep gradient prior network for DEM super-resolution: Transfer learning from image to DEM
Z Xu, Z Chen, W Yi, Q Gui, W Hou, M Ding - ISPRS Journal of …, 2019 - Elsevier
Digital elevation model (DEM) super-resolution (SR) aims to increase the spatial resolution
of a DEM through data processing, rather than using sensors with higher accuracy. Inspired …
of a DEM through data processing, rather than using sensors with higher accuracy. Inspired …
TTSR: A transformer-based topography neural network for digital elevation model super-resolution
Digital elevation models (DEMs) are crucial geographical data sources, whereas the
resolution of commonly used DEM products is low and cannot meet the requirement of …
resolution of commonly used DEM products is low and cannot meet the requirement of …
[HTML][HTML] A large scale Digital Elevation Model super-resolution Transformer
Abstract The Digital Elevation Model (DEM) super-resolution approach aims to improve the
spatial resolution or detail of an existing DEM by applying techniques such as machine …
spatial resolution or detail of an existing DEM by applying techniques such as machine …
[HTML][HTML] Super-resolution for terrain modeling using deep learning in high mountain Asia
Abstract High Mountain Asia (HMA) is characterized by some of the most complex and
rugged terrain conditions in the world. However, high resolution terrain data are not easy to …
rugged terrain conditions in the world. However, high resolution terrain data are not easy to …
[HTML][HTML] A DEM super-resolution reconstruction network combining internal and external learning
X Lin, Q Zhang, H Wang, C Yao, C Chen, L Cheng… - Remote Sensing, 2022 - mdpi.com
The study of digital elevation model (DEM) super-resolution reconstruction algorithms has
solved the problem of the need for high-resolution DEMs. However, the DEM super …
solved the problem of the need for high-resolution DEMs. However, the DEM super …
[HTML][HTML] Comparison of DEM super-resolution methods based on interpolation and neural networks
High-resolution digital elevation models (DEMs) play a critical role in geospatial databases,
which can be applied to many terrain-related studies such as facility siting, hydrological …
which can be applied to many terrain-related studies such as facility siting, hydrological …