The D-CNN-LSTM Autoencoder method optimizes the anomaly detection rate for all of the anomalies, specifically in the case of low magnitude anomalies, enhancing F1-score up to 18.12% in single types of ...

A research team at Texas A&M University is studying the use of Siri-like virtual assistant technology for use in space. The ...

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

CNN-based adversarial machine learning models are proposed to drive the innovation of anomaly detection techniques under Industry 5.0. However, the generalization inherent in the model is inadequate ...