Recent advances in sensor and mobile devices have enabled an unprecedented increase
in the availability and collection of urban trajectory data, thus increasing the demand for …

Rapid advance of location acquisition technologies boosts the generation of trajectory data,
which track the traces of moving objects. A trajectory is typically represented by a sequence …

Trajectories of moving objects are collected in many applications. Raw trajectory data is
typically very large, and has to be simplified before use. In this paper, we introduce the …

It is important for maritime authorities to effectively classify and identify unknown types of
ships in historical trajectory data. This paper uses a logistic regression model to construct a …

In trajectory classification tasks, the challenge is to find the subtrajectories or a set of
features that better discriminate the class. However, there is a lack of robustness in existing …

Several methods for trajectory classification build models exploring trajectory global
features, such as the average and the standard deviation of speed and acceleration, but for …

In the last few years trajectory classification has been applied to many real problems,
basically considering the dimensions of space and time or attributes inferred from these …

Current airspace has limited resources, and the widespread use of unmanned aerial
vehicles (UAVs) increases airspace density, which is already crowded with manned aircraft …

With the rapid development of digital technologies, location-aware technologies have
helped increase trajectory data availability that results from tracking moving objects …

In the last decade, trajectory classification has received significant attention. The vast
amount of data generated on social media, the use of sensor networks, IOT devices and …