A multidimensional Bayesian architecture for real-time anomaly detection and recovery in mobile robot sensory systems.
Manuel Castellano-QueroManuel Castillo-LópezJuan-Antonio Fernández-MadrigalVicente Arévalo-EspejoHolger VoosAlfonso García-CerezoPublished in: Eng. Appl. Artif. Intell. (2023)
Keyphrases
- anomaly detection
- real time
- mobile robot
- sensory systems
- intrusion detection
- detecting anomalies
- network intrusion detection
- anomalous behavior
- moving target
- detecting anomalous
- detect anomalies
- network anomaly detection
- network traffic
- one class support vector machines
- intrusion detection system
- image processing
- data assimilation
- neural network
- unsupervised learning
- bayesian networks
- maximum likelihood
- signal processing
- optical flow
- negative selection algorithm
- training set
- machine learning
- cumulative sum