Artificial intelligence is applied to many fields and contributes to many important applications
and research areas, such as intelligent data processing, natural language processing …

To ensure the secure operation of space assets, it is crucial to employ ground and/or space-
based surveillance sensors to observe a diverse array of anthropogenic space objects …

The recent proliferation of resident space objects (RSOs) in low Earth orbit (LEO) threatens
the sustainability of space as a resource and requires persistent monitoring to avoid …

The increasing number of Resident Space Objects poses a serious threat to the safe
operation of satellites. Alongside with mitigation policies, it is fundamental to predict the …

Abstract The field of Space Situational Awareness (SSA) has progressed over the last few
decades with new sensors coming online, the development of new approaches for making …

This paper presents a data driven approach to space object characterisation through the
application of machine learning techniques to observational light curve data. One …

In this paper, we present an end-to-end approach that employs machine learning
techniques and Ontology-based Bayesian Networks (BN) to characterize the behavior of …

The deployment of artificial neural networks (ANNs) on small satellites will improve space
situational awareness (SSA) where scarce radio resources limits the interactions between …

Temporal variations of apparent magnitude, called light curves, are observational statistics
of interest captured by telescopes over long periods of time. Light curves afford the …

Astronomical images collected by ground-based telescopes suffer from degradation and
perturbations attributed to atmospheric turbulence. We investigate the application of …