Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...

In this study, the focus is concentrated on the detection of anomalous network traffic (or intrusions) from flow-based data using unsupervised deep learning methods with semi-supervised learning ...

Jang et al. [36] introduced a Convolutional Variational Autoencoder (CVAE) that models the variability in ECG patterns through learned latent distributions, facilitating clustering and anomaly ...

Anomaly detection is one of the many challenging areas in cybersecurity. The anomaly can occur in many forms, such as fraudulent credit card transactions, network intrusions, and anomalous imageries ...

The autoencoder provides an anomaly detection algorithm for radiation treatment planning. It can detect a very small percentage of abnormal plans in a large number of radiotherapy plans with high ...