Anomaly detection is an active area of research with numerous methods and applications.
This survey reviews the state-of-the-art of data-driven anomaly detection techniques and …

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 …

Safety is key to civil aviation. To further improve its already respectable safety records, the
airline industry is transitioning towards a proactive approach which anticipates and mitigates …

Anomaly Detection in multivariate, time-series data collected from aircraft's Flight Data
Recorder (FDR) or Flight Operational Quality Assurance (FOQA) data provide a powerful …

The presence of incorrect data leads to the decrease of condition-monitoring big data
quality. As a result, unreliable or misleading results are probably obtained by analyzing …

Models for predicting aircraft motion are an important component of modern aeronautical
systems. These models help aircraft plan collision avoidance maneuvers and help conduct …

We present a new approach to separate air traffic trajectories in an area constrained by
operational procedures. This technique is applied on a set of real trajectories in Toulouse …

Monitoring aircraft performance in a fleet is fundamental to ensure optimal operation and
promptly detect anomalies that can increase fuel consumption or compromise flight safety …

Efficient planning of airport capacity is key for the successful accomplishment of traffic flow
management. Yet, the dynamic and uncertain behavior of capacity-determining factors …

Predictive maintenance has received considerable attention in the aviation industry where
costs, system availability and reliability are major concerns. In spite of recent advances …