Craters are one of the most important morphological features in planetary exploration. To
that extent, detecting, mapping and counting craters is a mainstream process in planetary …

Traditional vision-based navigation algorithms are highly affected from non-nominal
conditions, which comprise illumination conditions and environmental uncertainties. Thanks …

Craters are one of the most prominent features on planetary surfaces, used in applications
such as age estimation, hazard detection, and spacecraft navigation. Crater detection is a …

This paper introduces a new GeoAI solution to support automated mapping of global craters
on the Mars surface. Traditional crater detection algorithms suffer from the limitation of …

Crater detection is widely used in terrain relative navigation, which can help scientists target
a spacecraft's position and estimate the age of a planet. However, high-performance crater …

The growing ferment towards enhanced autonomy on-board spacecrafts is driving the
research of leading space agencies. Concurrently, the rapid developments of Artificial …

The integration of artificial intelligence (AI) technologies, particularly machine learning (ML),
with geotechnical engineering is transforming the landscape of infrastructure development …

Existing crater detection methods are typically carried out in the same domain where the
training and testing data are drawn from an identical distribution. However, this means that …

Craters are topographic structures resulting from impactors striking the surface of planetary
bodies. This paper proposes a novel way of simultaneously utilizing optical images, digital …

Crater extraction and recognition is an important research content of deep space planetary
science. Traditional crater detection algorithms (CDAs) are mainly based on crater feature …