A graph neural network for small-area estimation: integrating spatial regularisation, heterogeneous spatial units, and Bayesian inference
Lunar craters are important geomorphological features, that provide valuable insights into lunar morphology, geology, and impact processes. However, the current understanding of lunar craters of different sizes, especially smaller craters (diameter <5 km), is still incomplete. The lack of understanding of small lunar craters affects our understanding of the lunar surface and its geological history. Therefore, in this study, we propose a deep learning Crater Detection Algorithms (CDA), called Lunar Topographic Knowledge Attention U-Net (LTKAU-Net) that integrates a Digital Elevation Model (DEM) and topographic knowledge.
Dec 29, 2025
