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Detection of anomalous vehicle trajectories using federated learning

  • Published:2022-04 Issue: Volume:4 Page:100013
  • ISSN:2667-3932
  • Container-title:ISPRS Open Journal of Photogrammetry and Remote Sensing
  • language:en
  • Short-container-title:ISPRS Open Journal of Photogrammetry and Remote Sensing

Author:

Koetsier Christian,Fiosina JelenaORCID,Gremmel Jan N.,Müller Jörg P.,Woisetschläger David M.,Sester Monika

Publisher

Elsevier BV

Reference59 articles.

1. The limits to collaboration across four of the most innovative UK industries;Audretsch;Br. J. Manag.,2020

2. Fedpacket: A Federated Learning Approach to Mobile Packet Classification;Bakopoulou,2021

3. Trajectory outlier detection: algorithms, taxonomies, evaluation, and open challenges;Belhadi;ACM Trans. Manage. Inf. Syst.,2020

4. Hybrid group anomaly detection for sequence data: application to trajectory data analytics;Belhadi;IEEE Trans. Intell. Transport. Syst.,2021

5. Personalized and private peer-to-peer machine learning;Bellet,2018

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1. The Challenge of Data Analytics with Climate-neutral Urban Mobility (Vision Paper);ACM Transactions on Spatial Algorithms and Systems;2024-06-30

2. Federated Learning for Anomaly Detection in Maritime Movement Data;2024 25th IEEE International Conference on Mobile Data Management (MDM);2024-06-24

3. FRAnomaly: flow-based rapid anomaly detection from images;Applied Intelligence;2024-02

4. Deep reinforcement learning for base station switching scheme with federated LSTM‐based traffic predictions;ETRI Journal;2024-01-12

5. Federated Anomaly Detection with Isolation Forest for IoT Network Traffics;2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS);2023-12-17
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