Landslide susceptibility assessment (LSA) is of paramount importance in
...
Our work presents a novel spectrum-inspired learning-based approach for
...
The lack of façade structures in photogrammetric mesh models renders the...
Automatic and periodic recompiling of building databases with up-to-date...
Most urban applications necessitate building footprints in the form of
c...
The accurate representation of 3D building models in urban environments ...
Deep learning has achieved great success in learning features from massi...
Do we on the right way for remote sensing image understanding (RSIU) by
...
Deep learning methods are notoriously data-hungry, which requires a larg...
Humans' continual learning (CL) ability is closely related to Stability
...
Graph neural networks (GNNs) have achieved great success in many graph-b...
A new learning paradigm, self-supervised learning (SSL), can be used to ...
One of the key problems of GNNs is how to describe the importance of nei...
Detecting the changes of buildings in urban environments is essential.
E...
Photogrammetric mesh models obtained from aerial oblique images have bee...
In this paper, we propose a novel minimum gravitational potential energy...
Integration of aerial and ground images has been proved as an efficient
...
Regularized arrangement of primitives on building façades to aligned
loc...
Precision mapping of landslide inventory is crucial for hazard mitigatio...
Accurately and efficiently extracting building footprints from a wide ra...
Middle-echo, which covers one or a few corresponding points, is a specif...
Catastrophic forgetting is a challenge issue in continual learning when ...
The key factor of scene change detection is to learn effective feature t...
While image registration has been studied in remote sensing community fo...