2 citations · 2 across the 3 of their papers we have counts for
3 papers
Time series Forecasting to detect anomalous behaviours in Multiphase Flow Meters
Tommaso Barbariol, Davide Masiero, Enrico Feltresi +1
An Anomaly Detection (AD) System for Self-diagnosis has been developed for Multiphase Flow Meter (MPFM). The system relies on machine learning algorithms for time series forecastin…
Active Learning-based Isolation Forest (ALIF): Enhancing Anomaly Detection in Decision Support Systems
Elisa Marcelli, Tommaso Barbariol, Gian Antonio Susto
The detection of anomalous behaviours is an emerging need in many applications, particularly in contexts where security and reliability are critical aspects. While the definition o…
TiWS-iForest: Isolation Forest in Weakly Supervised and Tiny ML scenarios
Tommaso Barbariol, Gian Antonio Susto
Unsupervised anomaly detection tackles the problem of finding anomalies inside datasets without the labels availability; since data tagging is typically hard or expensive to obtain…