Deep learning for trajectory data management and mining: A survey and beyond

W Chen, Y Liang, Y Zhu, Y Chang, K Luo… - arXiv preprint arXiv …, 2024 - arxiv.org
Trajectory computing is a pivotal domain encompassing trajectory data management and
mining, garnering widespread attention due to its crucial role in various practical …

Online anomalous trajectory detection with deep generative sequence modeling

Y Liu, K Zhao, G Cong, Z Bao - 2020 IEEE 36th International …, 2020 - ieeexplore.ieee.org
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 …

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 …

[HTML][HTML] Towards automatic anomaly detection in fisheries using electronic monitoring and automatic identification system

D Acharya, M Farazi, V Rolland, L Petersson… - Fisheries …, 2024 - Elsevier
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 …

DeepTEA: Effective and efficient online time-dependent trajectory outlier detection

X Han, R Cheng, C Ma, T Grubenmann - Proceedings of the VLDB …, 2022 - dl.acm.org
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 …

A data-driven method for falsified vehicle trajectory identification by anomaly detection

SE Huang, Y Feng, HX Liu - Transportation research part C: emerging …, 2021 - Elsevier
The vehicle-to-infrastructure (V2I) communications enable a wide range of new applications,
which bring prominent benefits to the transportation system. However, malicious attackers …

DiffTAD: Denoising diffusion probabilistic models for vehicle trajectory anomaly detection

C Li, G Feng, Y Li, R Liu, Q Miao, L Chang - Knowledge-Based Systems, 2024 - Elsevier
Vehicle trajectory anomaly detection plays an essential role in the fields of traffic video
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 …

[HTML][HTML] Deep learning framework for congestion detection at public places via learning from synthetic data

S Basalamah, SD Khan, E Felemban, A Naseer… - Journal of King Saud …, 2023 - Elsevier
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 …

[PDF][PDF] Open Anomalous Trajectory Recognition via Probabilistic Metric Learning.

Q Gao, X Wang, C Liu, G Trajcevski, L Huang, F Zhou - IJCAI, 2023 - ijcai.org
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 …