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Online anomaly detection in unmanned vehicles
Eliahu Khalastchi
,
Gal A. Kaminka
, Meir Kalech
, Raz Lin
Department of Computer Science and Artificial Intelligence
Bar Ilan Robotics Consortium (BIRC)
Ben-Gurion University of the Negev
Research output
:
Contribution to conference
›
Paper
›
peer-review
40
Scopus citations
Overview
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Student theses
(1)
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Dive into the research topics of 'Online anomaly detection in unmanned vehicles'. Together they form a unique fingerprint.
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Keyphrases
Online Anomaly Detection
100%
Unmanned Vehicle
100%
Artificial Intelligence
50%
Mahalanobis Distance
50%
Robotics
50%
Task Failure
50%
Internal Measurement
50%
Autonomous Robots
50%
Online Selection
50%
Physical Faults
50%
Verified Software
50%
Vacuum Cleaning Robot
50%
General Terms
50%
Unmanned Autonomous Vehicles
50%
Flight Simulator
50%
Large Dimension
50%
Subject Descriptors
50%
Sensor Measurement
50%
Correlated Measurements
50%
Anomaly Detection System
50%
Making Decisions
50%
Unmanned Aerial Vehicle
50%
Computer Science
Robotics
100%
Anomaly Detection
100%
Robot
66%
Physical Fault
33%
Autonomous Vehicles
33%
Detection Method
33%
Mahalanobis Distance
33%
Artificial Intelligence
33%
Unmanned Aerial Vehicle
33%