CONVOLUTIONAL NEURAL NETWORK BASED DEM SUPER RESOLUTION

28 citations as recorded by crossref.

1. T2-cGAN: A new modeling paradigm for joint DEM spatial interpolation and super-resolution reconstruction Z. Huo et al.
2. DDMAFN: A Progressive Dual-Domain Super-Resolution Network for Digital Elevation Model Based on Multi-Scale Feature Fusion B. He et al.
3. Super-resolution reconstruction of the 1 arc-second Australian coastal DEM dataset B. Zhang et al.
4. Sliding Windows Method Based on Terrain Self-Similarity for Higher DEM Resolution in Flood Simulating Modeling Q. Yin et al.
5. JSPSR: Joint Spatial Propagation Super-Resolution Networks for Enhancement of Bare-Earth Digital Elevation Models from Global Data X. Cai & M. Wilson
6. LIE-DSM: Leveraging Single Remote Sensing Imagery to Enhance Digital Surface Model Resolution S. Zhang et al.
7. Multi-modal DEM super-resolution using relative depth: A new benchmark and beyond W. Huang et al.
8. TTSR: A Transformer-Based Topography Neural Network for Digital Elevation Model Super-Resolution Y. Wang et al.
9. Terrain Self-Similarity-Based Transformer for Generating Super Resolution DEMs X. Zheng et al.
10. D-SRGAN: DEM Super-Resolution with Generative Adversarial Networks B. Demiray et al.
11. Research on High-Resolution Modeling of Satellite-Derived Marine Environmental Parameters Based on Adaptive Global Attention R. Cui et al.
12. An Enhanced Double-Filter Deep Residual Neural Network for Generating Super Resolution DEMs A. Zhou et al.
13. Unmixing frequency features for DEM super resolution Z. Wen et al.
14. A DEM Super-Resolution Reconstruction Network Combining Internal and External Learning X. Lin et al.
15. An ensemble learning framework for generating high-resolution regional DEMs considering geographical zoning X. Han et al.
16. Multi-Branch Deep Neural Network for Bed Topography of Antarctica Super-Resolution: Reasonable Integration of Multiple Remote Sensing Data Y. Cai et al.
17. Super-Resolution Remote Sensing Datasets for Application to Caral–Supe Archeological Sites Employing SAR and DEMs J. Kim & R. Singh
18. Comparison of DEM Super-Resolution Methods Based on Interpolation and Neural Networks Y. Zhang & W. Yu
19. DEM super-resolution framework based on deep learning: decomposing terrain trends and residuals H. Wang et al.
20. Deep learning methods applied to digital elevation models: state of the art J. Ruiz-Lendínez et al.
21. A Global-Information-Constrained Deep Learning Network for Digital Elevation Model Super-Resolution X. Han et al.
22. A Transformer-Unet Generative Adversarial Network for the Super-Resolution Reconstruction of DEMs X. Zheng et al.
23. Real-World DEM Super-Resolution Based on Generative Adversarial Networks for Improving InSAR Topographic Phase Simulation Z. Wu et al.
24. Exploring the integration of auxiliary modal information from remote sensing images for DEM super-resolution B. Gao et al.
25. Super-resolution reconstruction of a digital elevation model based on a deep residual network D. Jiao et al.
26. An Enhanced Residual Feature Fusion Network Integrated with a Terrain Weight Module for Digital Elevation Model Super-Resolution G. Chen et al.
27. A rapid high-resolution multi-sensory urban flood mapping framework via DEM upscaling W. Tan et al.
28. A Seabed Terrain Feature Extraction Transformer for the Super-Resolution of the Digital Bathymetric Model W. Cai et al.