Unmanned Aerial Vehicle Anomaly Detection Based on Causality-Enhanced Graph Neural Networks
With the widespread application of unmanned aerial vehicles (UAVs), the safety detection system of UAVs has created an urgent need for anomaly detection technology. As a direct representation of system health status, flight data contain critical status information, driving data-driven methods to gra...
Saved in:
Main Authors: | Chen Feng, Jun Fan, Zhiliang Liu, Guang Jin, Siya Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-06-01
|
Series: | Drones |
Subjects: | |
Online Access: | https://www.mdpi.com/2504-446X/9/6/408 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
MODELLING GROUP ACTION OF UNMANNED AERIAL VEHICLES
by: S. V. Korevanov
Published: (2016-11-01) -
MODELLING GROUP ACION UNMANNED AERIAL VEHICLES
by: S. V. Korevanov
Published: (2016-11-01) -
Algorithm for Calculating the Flight Time of an Unmanned Aerial Vehicle for Aerial Photography
by: R. K. Kurbanov
Published: (2023-04-01) -
METHODOLOGY FOR ACCOUNTING THE INFLUENCE OF METEOROLOGICAL FACTORS ON THE EFFICIENCY OF APPLICATION OF UNMANNED AERIAL VEHICLES ON THE BASIS OF SYSTEM ANALYSIS
by: I. E. Kuznetsov, et al.
Published: (2018-12-01) -
History of unmanned aircraft flight controller development
by: Yu. S. Tsench, et al.
Published: (2023-09-01)