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Tommaso Barbariol
Tommaso Barbariol
Ph.D. Student, University of Padova
Bestätigte E-Mail-Adresse bei phd.unipd.it
Titel
Zitiert von
Zitiert von
Jahr
A review of tree-based approaches for anomaly detection
T Barbariol, FD Chiara, D Marcato, GA Susto
Control Charts and Machine Learning for Anomaly Detection in Manufacturing …, 2022
382022
Self-diagnosis of multiphase flow meters through machine learning-based anomaly detection
T Barbariol, E Feltresi, GA Susto
Energies 13 (12), 3136, 2020
332020
Machine learning approaches for anomaly detection in multiphase flow meters
T Barbariol, E Feltresi, GA Susto
IFAC-PapersOnLine 52 (11), 212-217, 2019
222019
TiWS-iForest: Isolation forest in weakly supervised and tiny ML scenarios
T Barbariol, GA Susto
Information Sciences 610, 126-143, 2022
192022
Uncertainty estimation for machine learning models in multiphase flow applications
L Frau, GA Susto, T Barbariol, E Feltresi
Informatics 8 (3), 58, 2021
72021
Classifying circumnutation in pea plants via supervised machine learning
Q Wang, T Barbariol, GA Susto, B Bonato, S Guerra, U Castiello
Plants 12 (4), 965, 2023
62023
A machine learning-based system for self-diagnosis multiphase flow meters
T Barbariol, E Feltresi, GA Susto
International Petroleum Technology Conference, D021S042R003, 2020
52020
Bayesian active learning isolation forest (B-ALIF): A weakly supervised strategy for anomaly detection
D Sartor, T Barbariol, GA Susto
Engineering Applications of Artificial Intelligence 130, 107671, 2024
42024
A revised isolation forest procedure for anomaly detection with high number of data points
E Marcelli, T Barbariol, V Savarino, A Beghi, GA Susto
2022 IEEE 23rd Latin American Test Symposium (LATS), 1-5, 2022
32022
Active Learning-based Isolation Forest (ALIF): Enhancing Anomaly Detection in Decision Support Systems
E Marcelli, T Barbariol, GA Susto
arXiv preprint arXiv:2207.03934, 2022
32022
Validity and consistency of MPFM data through a Machine Learning-based system
T Barbariol, E Feltresi, GA Susto
Proceeding 37th North Sea Flow measurement Wor shop, 2019
22019
Active Learning-based Isolation Forest (ALIF): Enhancing Anomaly Detection with Expert Feedback
E Marcelli, T Barbariol, D Sartor, GA Susto
Information Sciences, 121012, 2024
12024
Improving Anomaly Detection for Industrial Applications
T Barbariol
Università degli studi di Padova, 2023
12023
Sensor fusion and machine learning techniques to improve water cut measurements accuracy in multiphase application
T Barbariol, E Feltresi, GA Susto, D Tescaro, S Galvanin
SPE Annual Technical Conference and Exhibition?, D022S061R003, 2020
12020
Time Series Forecasting to Detect Anomalous Behavior in Multiphase Flow Meters
T Barbariol, D Masiero, M Fanan, E Feltresi, GA Susto
2024 IEEE 8th Forum on Research and Technologies for Society and Industry …, 2024
2024
Unveiling Circumnutation in Pea Plants via Supervised Machine Learning
Q Wang, T Barbariol, GA Susto, B Bonato, S Guerra, U Castiello
Preprints, 2023
2023
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