2 citations · 2 across the 5 of their papers we have counts for
5 papers
Staypoint Detection from Noisy Trajectory Data [Experiment Paper]
Lance Kennedy, Hossein Amiri, Yueyang Liu +9
Detecting staypoints from raw trajectory data is fundamental to numerous spatial computing applications. This process transforms raw numeric sequences of geolocations into semantic…
SF-LIFE: A Large-Scale Simulated Movement Dataset for the San Francisco Bay Area
Chanuka Algama, Taylor Anderson, Henrique Ferraz de Arruda +14
We introduce SF-LIFE, a large-scale simulated movement dataset designed to accelerate research in transportation, mobility, and machine learning. The dataset contains 3,024,000,000…
Training Machine Learning Models on Human Spatio-temporal Mobility Data: An Experimental Study [Experiment Paper]
Yueyang Liu, Lance Kennedy, Ruochen Kong +2
Individual-level human mobility prediction has emerged as a significant topic of research with applications in infectious disease monitoring, child, and elderly care. Existing stud…
Neural Collaborative Filtering to Detect Anomalies in Human Semantic Trajectories
Yueyang Liu, Lance Kennedy, Hossein Amiri +1
Human trajectory anomaly detection has become increasingly important across a wide range of applications, including security surveillance and public health. However, existing traje…
Kinematic Detection of Anomalies in Human Trajectory Data
Lance Kennedy, Andreas Züfle
Historically, much of the research in understanding, modeling, and mining human trajectory data has focused on where an individual stays. Thus, the focus of existing research has b…