| Self-diagnosis of multiphase flow meters through machine learning-based anomaly detection T Barbariol, E Feltresi, GA Susto Energies 13 (12), 3136, 2020 | 23 | 2020 |
| 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 | 19 | 2022 |
| Machine learning approaches for anomaly detection in multiphase flow meters T Barbariol, E Feltresi, GA Susto IFAC-PapersOnLine 52 (11), 212-217, 2019 | 19 | 2019 |
| TiWS-iForest: Isolation forest in weakly supervised and tiny ML scenarios T Barbariol, GA Susto Information Sciences 610, 126-143, 2022 | 11 | 2022 |
| Uncertainty estimation for machine learning models in multiphase flow applications L Frau, GA Susto, T Barbariol, E Feltresi Informatics 8 (3), 58, 2021 | 6 | 2021 |
| A machine learning-based system for self-diagnosis multiphase flow meters T Barbariol, E Feltresi, GA Susto International Petroleum Technology Conference, D021S042R003, 2020 | 5 | 2020 |
| 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 | 2 | 2022 |
| 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 | 2 | 2019 |
| 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 | 1 | 2020 |
| Improving Anomaly Detection for Industrial Applications T Barbariol Università degli studi di Padova, 2023 | | 2023 |
| 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 | | 2023 |
| Unveiling Circumnutation in Pea Plants via Supervised Machine Learning Q Wang, T Barbariol, GA Susto, B Bonato, S Guerra, U Castiello Preprints, 2023 | | 2023 |
| Time series Forecasting to detect anomalous behaviours in Multiphase Flow Meters T Barbariol, D Masiero, E Feltresi, GA Susto arXiv preprint arXiv:2301.00014, 2022 | | 2022 |
| 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 | | 2022 |
Gian Antonio SustoAssociate Professor @ University of Padova, Co-founder @ StatwolfBestätigte E-Mail-Adresse bei dei.unipd.it
