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A survey on federated learning in intelligent transportation systems
The development of Intelligent Transportation System (ITS) has brought about
comprehensive urban traffic information that not only provides convenience to urban …
comprehensive urban traffic information that not only provides convenience to urban …
Deep learning for trajectory data management and mining: A survey and beyond
Trajectory computing is a pivotal domain encompassing trajectory data management and
mining, garnering widespread attention due to its crucial role in various practical …
mining, garnering widespread attention due to its crucial role in various practical …
Difftraj: Generating gps trajectory with diffusion probabilistic model
Pervasive integration of GPS-enabled devices and data acquisition technologies has led to
an exponential increase in GPS trajectory data, fostering advancements in spatial-temporal …
an exponential increase in GPS trajectory data, fostering advancements in spatial-temporal …
FedPT-V2G: Security enhanced federated transformer learning for real-time V2G dispatch with non-IID data
The rising popularity of electric vehicles (EVs) underscores the potential of vehicle-to-grid
(V2G) technology to contribute to load peak-shaving, valley-filling, and photovoltaic (PV) self …
(V2G) technology to contribute to load peak-shaving, valley-filling, and photovoltaic (PV) self …
Synmob: Creating high-fidelity synthetic gps trajectory dataset for urban mobility analysis
Urban mobility analysis has been extensively studied in the past decade using a vast
amount of GPS trajectory data, which reveals hidden patterns in movement and human …
amount of GPS trajectory data, which reveals hidden patterns in movement and human …
[PDF][PDF] A survey on uncertainty quantification methods for deep neural networks: An uncertainty source perspective
A Survey on Uncertainty Quantification Methods for Deep Neural Networks: An Uncertainty
Source's Perspective Page 1 A Survey on Uncertainty Quantification Methods for Deep Neural …
Source's Perspective Page 1 A Survey on Uncertainty Quantification Methods for Deep Neural …
Anomalous sub-trajectory detection with graph contrastive self-supervised learning
Some anomalous vehicle trajectories may contain fraudulent behavior or traffic accident
information. Existing research mostly starts from a global view, treating the entire trajectory …
information. Existing research mostly starts from a global view, treating the entire trajectory …
[HTML][HTML] Towards trustworthy cybersecurity operations using Bayesian Deep Learning to improve uncertainty quantification of anomaly detection
Uncertainty quantification of cybersecurity anomaly detection results provides critical
guidance for decision makers on whether or not to accept the results. Improving the …
guidance for decision makers on whether or not to accept the results. Improving the …
Filtering limited automatic vehicle identification data for real-time path travel time estimation without ground truth
Automatic Vehicle Identification (AVI) technology has been widely used for real-time path
travel time estimation. For a study path equipped with AVI sensors at both ends, the …
travel time estimation. For a study path equipped with AVI sensors at both ends, the …
[HTML][HTML] Uncertainty-aware probabilistic graph neural networks for road-level traffic crash prediction
Traffic crashes present substantial challenges to human safety and socio-economic
development in urban areas. Develo** a reliable and responsible traffic crash prediction …
development in urban areas. Develo** a reliable and responsible traffic crash prediction …