Deep Residual Shrinkage Network Based Fault Diagnosis for Quadrotor UAV Formation System
Author:
Affiliation:
1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics,Nanjing,P. R. China,211106
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10606543/10606546/10606765.pdf?arnumber=10606765
Reference13 articles.
1. Cooperative forest fire surveillance using a team of small unmanned air vehicles
2. Sense and avoid technologies with applications to unmanned aircraft systems: Review and prospects
3. Real-Time Fault Detection for UAV Based on Model Acceleration Engine
4. On-board Deep-learning-based Unmanned Aerial Vehicle Fault Cause Detection and Identification
5. A hybrid feature model and deep learning based fault diagnosis for unmanned aerial vehicle sensors
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