In recent decades, deep learning (DL) has become a rapidly growing research direction,
redefining the state-of-the-art performances in a wide range of techniques, such as object …

The use of sensor technology constantly gathering aircrafts' status data has promoted the
rapid development of data-driven solutions in aerospace engineering. These methods …

Data science, and machine learning in particular, is rapidly transforming the scientific and
industrial landscapes. The aerospace industry is poised to capitalize on big data and …

Within the next several years, there will be a high level of autonomous technology that will
be available for widespread use, which will reduce labor costs, increase safety, save energy …

Traditional control methods are inadequate in many deployment settings involving
autonomous control of Cyber-Physical Systems (CPS). In such settings, CPS controllers …

Deep learning is recently showing outstanding results for solving a wide variety of robotic
tasks in the areas of perception, planning, localization, and control. Its excellent capabilities …

As data sets grow, leveraging machines to learn valuable patterns from structured data can
be extremely powerful. The volume of data is too large for comprehensive analysis, and the …

Detect-and-Avoid (DAA) capabilities are critical for safe operations of unmanned aircraft
systems (UAS). This paper introduces, AirTrack, a real-time vision-only detect and tracking …

This review covers the new developments in machine learning (ML) that are impacting the
multi-disciplinary area of aerospace engineering, including fundamental fluid dynamics …

The vibration of a wing structure in the air reflects coupled aerodynamic–mechanical
responses under varying flight states that are defined by the angle of attack and airspeed. It …