Abstract Generative Adversarial Networks (GANs) are a type of deep neural network that
have achieved many state-of-the-art results for generative tasks. GANs can be useful in the …

Abstract Three-dimensional (3D) building roof reconstruction from airborne LiDAR point
clouds is an important task in photogrammetry and computer vision. To automatically …

Automated 3D reconstruction based on satellite images has become a research hotspot at
the interdisciplinary of photogrammetry and computer vision. The 3D results based on …

There has been substantial progress in small object detection in aerial images in recent
years, due to the extensive applications and improved performances of convolutional neural …

Modern optical satellite sensors enable high-resolution stereo reconstruction from space.
But the challenging imaging conditions when observing the Earth from space push stereo …

Abstract Recently, Digital Twins solutions have attracted a growing interest as a fundamental
paradigm for managing data driven processes on smart cities. They are complex modelling …

High-rise building areas (HRBs) provide significant social and environmental services and
play a crucial role in modern urbanization. The large-scale and long-term spatial distribution …

Software accuracy and efficiency checks are becoming of paramount interest to system
users before utilization. As a result, twenty-first-century programmers are consciously …

Generative Adversarial Network (GAN), deemed as a powerful deep-learning-based silver
bullet for intelligent data generation, has been widely used in multi-disciplines. Furthermore …

For large-scale 3D building reconstruction, there have been several approaches to utilizing
multi-view satellite imagery to produce a digital surface model (DSM) for height information …