ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2505.21703
  4. Cited By
A Joint Reconstruction-Triplet Loss Autoencoder Approach Towards Unseen Attack Detection in IoV Networks

A Joint Reconstruction-Triplet Loss Autoencoder Approach Towards Unseen Attack Detection in IoV Networks

IEEE Internet of Things Journal (IEEE IoT J.), 2025
27 May 2025
Julia Boone
Tolunay Seyfi
Fatemeh Afghah
    AAML
ArXiv (abs)PDFHTML

Papers citing "A Joint Reconstruction-Triplet Loss Autoencoder Approach Towards Unseen Attack Detection in IoV Networks"

2 / 2 papers shown
Why Pool When You Can Flow? Active Learning with GFlowNets
Why Pool When You Can Flow? Active Learning with GFlowNets
Renfei Zhang
Mohit Pandey
Artem Cherkasov
Martin Ester
98
1
0
31 Aug 2025
Securing Swarms: Cross-Domain Adaptation for ROS2-based CPS Anomaly Detection
Securing Swarms: Cross-Domain Adaptation for ROS2-based CPS Anomaly Detection
Julia Boone
Fatemeh Afghah
AAML
118
1
0
20 Aug 2025
1