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 …
Online anomalous trajectory detection with deep generative sequence modeling
Detecting anomalous trajectory has become an important and fundamental concern in many
real-world applications. However, most of the existing studies 1) cannot handle the …
real-world applications. However, most of the existing studies 1) cannot handle the …
GeoTrackNet—A Maritime Anomaly Detector Using Probabilistic Neural Network Representation of AIS Tracks and A Contrario Detection
D Nguyen, R Vadaine, G Hajduch… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Representing maritime traffic patterns and detecting anomalies from them are key to vessel
monitoring and maritime situational awareness. We propose a novel approach—referred to …
monitoring and maritime situational awareness. We propose a novel approach—referred to …
[HTML][HTML] Towards automatic anomaly detection in fisheries using electronic monitoring and automatic identification system
To ensure sustainable fisheries, many complex on-vessel activities are periodically
monitored to provide data to assist the assessment of stock status and ensure fishery …
monitored to provide data to assist the assessment of stock status and ensure fishery …
DeepTEA: Effective and efficient online time-dependent trajectory outlier detection
In this paper, we study anomalous trajectory detection, which aims to extract abnormal
movements of vehicles on the roads. This important problem, which facilitates understanding …
movements of vehicles on the roads. This important problem, which facilitates understanding …
A data-driven method for falsified vehicle trajectory identification by anomaly detection
The vehicle-to-infrastructure (V2I) communications enable a wide range of new applications,
which bring prominent benefits to the transportation system. However, malicious attackers …
which bring prominent benefits to the transportation system. However, malicious attackers …
DiffTAD: Denoising diffusion probabilistic models for vehicle trajectory anomaly detection
Vehicle trajectory anomaly detection plays an essential role in the fields of traffic video
surveillance, autonomous driving navigation, and taxi fraud detection. Deep generative …
surveillance, autonomous driving navigation, and taxi fraud detection. Deep generative …
A method for LSTM-based trajectory modeling and abnormal trajectory detection
Y Ji, L Wang, W Wu, H Shao, Y Feng - IEEE Access, 2020 - ieeexplore.ieee.org
Nowadays, massive data has been brought by the rapid development of technology. When
finding whether trajectory to be detected is abnormal under the premise of given normal …
finding whether trajectory to be detected is abnormal under the premise of given normal …
[HTML][HTML] Deep learning framework for congestion detection at public places via learning from synthetic data
Congestion in public places is one of the major problems in public transportation systems
and causes a high level of discomfort for the commuters. Traditionally, overcrowding is …
and causes a high level of discomfort for the commuters. Traditionally, overcrowding is …
[PDF][PDF] Open Anomalous Trajectory Recognition via Probabilistic Metric Learning.
Typically, trajectories considered anomalous are the ones deviating from usual (eg, traffic-
dictated) driving patterns. However, this closed-set context fails to recognize the unknown …
dictated) driving patterns. However, this closed-set context fails to recognize the unknown …