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Found 5 papers, 1 papers with code
MobilityDL: A Review of Deep Learning From Trajectory Data
Trajectory data combines the complexities of time series, spatial data, and (sometimes irrational) movement behavior.
Here Is Not There: Measuring Entailment-Based Trajectory Similarity for Location-Privacy Protection and Beyond
In this work, we present a different view on trajectory similarity by introducing a measure that utilizes logical entailment.
Towards eXplainable AI for Mobility Data Science
This paper presents our ongoing work towards XAI for Mobility Data Science applications, focusing on explainable models that can learn from dense trajectory data, such as GPS tracks of vehicles and vessels using temporal graph neural networks (GNNs) and counterfactuals.
Explainable Artificial Intelligence (XAI)
Explainable Models
Federated Learning for Predictive Maintenance and Quality Inspection in Industrial Applications
Data-driven machine learning is playing a crucial role in the advancements of Industry 4. 0, specifically in enhancing predictive maintenance and quality inspection.
From Simple Features to Moving Features and Beyond?
Mobility data science lacks common data structures and analytical functions.
Computers and Society E.1
