mlsanityData to 7 Oct 2026

DEM Super-Resolution with EfficientNetV2

arXiv 2109.09661 ↗First posted 20 Sep 2021eess.IV cs.CVcited by 5

Not on the map. Why?

Abstract (arXiv)

Efficient climate change monitoring and modeling rely on high-quality geospatial and environmental datasets. Due to limitations in technical capabilities or resources, the acquisition of high-quality data for many environmental disciplines is costly. Digital Elevation Model (DEM) datasets are such examples whereas their low-resolution versions are widely available, high-resolution ones are scarce. In an effort to rectify this problem, we propose and assess an EfficientNetV2 based model. The proposed model increases the spatial resolution of DEMs up to 16times without additional information.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 20 of its 34 references that are in the map. First posted on arXiv 20 Sep 2021.

Builds on

20 of 34 references.

References · 20

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  3. 2019EfficientNet: Rethinking Model Scaling for Convolutional Neural Networkscited by 6,415
  4. 2018MobileNetV2: Inverted Residuals and Linear Bottleneckscited by 4,773
  5. 2017MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applicationscited by 3,827
  6. 2019Searching for MobileNetV3cited by 1,984
  7. 2016Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Networkcited by 1,898
  8. 2017Enhanced Deep Residual Networks for Single Image Super-Resolutioncited by 1,543
  9. 2018ESRGAN: Enhanced Super-Resolution Generative Adversarial Networkscited by 1,250
  10. 2014Image Super-Resolution Using Deep Convolutional Networkscited by 1,218
  11. 2021EfficientNetV2: Smaller Models and Faster Trainingcited by 1,127
  12. 2015Accurate Image Super-Resolution Using Very Deep Convolutional Networkscited by 902
8 more
  1. 2016Accelerating the Super-Resolution Convolutional Neural Networkcited by 393
  2. 2019Deep Learning for Image Super-resolution: A Surveycited by 368
  3. 2015Deeply-Recursive Convolutional Network for Image Super-Resolutioncited by 317
  4. 2019Tackling Climate Change with Machine Learningcited by 264
  5. 2018A Fully Progressive Approach to Single-Image Super-Resolutioncited by 46
  6. 2020A Comprehensive Review of Deep Learning Applications in Hydrology and Water Resourcescited by 30
  7. 2020D-SRGAN: DEM Super-Resolution with Generative Adversarial Networkscited by 15
  8. 2021Short-term Hourly Streamflow Prediction with Graph Convolutional GRU Networkscited by 12

Built on by

Cited by year

Citing papers per year: 2023: 4; 2024: 1.

5 papers.

  1. 2023Artificial Intelligence-Enabled Intelligent Assistant for Personalized and Adaptive Learning in Higher Educationcited by 17
  2. 2023Performance of ChatGPT on the US Fundamentals of Engineering Exam: Comprehensive Assessment of Proficiency and Potential Implications for Professional Environmental Engineering Practicecited by 15
  3. 2023Platform-Independent and Curriculum-Oriented Intelligent Assistant for Higher Educationcited by 12
  4. 2023High-resolution Multi-spectral Image Guided DEM Super-resolution using Sinkhorn Regularized Adversarial Networkcited by 0
  5. 2024A Sinkhorn Regularized Adversarial Network for Image Guided DEM Super-resolution using Frequency Selective Hybrid Graph Transformercited by 0