… Anomaly detection is an important part of an Intelligent Transportation System. In … machine
learning techniques are used to detect anomalies in vehicle movements. These anomalies …

… There can be many types of possible attacks and anomaly that can affect the IoT system …
anomalies are predicted based on a different feature in the data set. Two machine learning …

… 3, we consider how similar the detection methods are to … of the phase space of resonant
anomalies. In Sect. 4, we … summary for machine learning-enhanced anomaly detection across all …

… Afterwards, the processed data are fed to the ML-based anomaly detection model for
detecting the fiber anomalies or faults. If a fiber anomaly is detected, an ML model for fault …

… for the anomaly detection problem. This allows us to compare different anomaly detection …
to propose a support vector machine (SVM) for anomaly detection for which we can easily …

… In this paper, we propose the AD-IoT system which uses an intelligent anomaly detection
method based on machine learning algorithms that can detect attacks with reducing the false …

… We conclude that anomaly detection can be performed with machine learning techniques in
EtherCAT protocol-based systems, which is one of the critical infrastructure systems where it …

… end, anomaly detection … machine learning. Most importantly, our results show that expert-based
data annotation is extremely valuable for anomaly detection based on machine learning. …

… by applying anomaly detection is the attempt to detect all … potential end users can be detected
earlier to minimise adverse … The end goal of anomaly detection is to provide a faster and …

… of anomaly detection for machine learning redshift estimation. Anomaly detection allows
the … Anomalous training examples may be photometric galaxies with incorrect spectroscopic …