SUSTO, GIAN ANTONIO
SUSTO, GIAN ANTONIO
Dipartimento di Ingegneria dell'Informazione - DEI
A Computer Vision-inspired Deep Learning Architecture for Virtual Metrology modeling with 2-Dimensional Data
2018 Maggipinto, Marco; Terzi, Matteo; Masiero, Chiara; Beghi, A.; Susto, G. A.
A Convolutional Autoencoder Approach for Feature Extraction in Virtual Metrology
2018 Maggipinto, Marco; Masiero, Chiara; Beghi, A.; Susto, G. A.
A Deep Convolutional Autoencoder-Based Approach for Anomaly Detection With Industrial, Non-Images, 2-Dimensional Data: A Semiconductor Manufacturing Case Study
2022 Maggipinto, Marco; Beghi, Alessandro; Susto, Gian Antonio
A deep learning approach for anomaly detection with industrial time series data: a refrigerators manufacturing case study
2019 Carletti, Mattia; Masiero, Chiara; Beghi, Alessandro; Susto, GIAN ANTONIO
A Dynamic Sampling Approach for Cost Reduction in Semiconductor Manufacturing
2018 Susto, G. A.; Maggipinto, M.; Zocco, F.; Mcloone, S.
A hidden-Gamma model-based filtering and prediction approach for monotonic health factors in manufacturing
2018 Susto, Gian Antonio; Schirru, Andrea; Pampuri, Simone; Beghi, Alessandro; De Nicolao, Giuseppe
A Methodology for Efficient Dynamic Spatial Sampling and Reconstruction of Wafer Profiles
2018 Mcloone, Sean; Johnston, Adrian; Susto, Gian Antonio
A multi-label Continual Learning framework to scale deep learning approaches for packaging equipment monitoring
2023 Dalle Pezze, Davide; Deronjic, Denis; Masiero, Chiara; Tosato, Diego; Beghi, Alessandro; Susto, Gian Antonio
A Predictive Maintenance System for Epitaxy Processes Based on Filtering and Prediction Techniques
2012 Susto, GIAN ANTONIO; Beghi, Alessandro; C., De Luca
A Self-Tuning KPCA-Based Approach to Fault Detection in Chiller Systems
2022 Simmini, F.; Rampazzo, M.; Peterle, F.; Susto, G. A.; Beghi, A.
A virtual metrology system based on least angle regression and statistical clustering
2013 Susto, GIAN ANTONIO; Beghi, Alessandro
AcME—Accelerated model-agnostic explanations: Fast whitening of the machine-learning black box
2023 Dandolo, David; Masiero, Chiara; Carletti, Mattia; Dalle Pezze, Davide; Susto, Gian Antonio
Active Learning-based Isolation Forest (ALIF): Enhancing anomaly detection with expert feedback
2024 Marcelli, E.; Barbariol, T.; Sartor, D.; Susto, G. A.
Adversarially Robust Fault Zone Prediction in Smart Grids With Bayesian Neural Networks
2024 Efatinasab, Emad; Sinigaglia, Alberto; Azadi, Nahal; Antonio Susto, Gian; Rampazzo, Mirco
Algorithmic fairness datasets: the story so far
2022 Fabris, Alessandro; Messina, Stefano; Silvello, Gianmaria; Susto, Gian Antonio
An Autoencoder-based Approach for Fault Detection in Multi-stage Manufacturing: a Sputter Deposition and Rapid Thermal Processing case study
2022 Jebril, H. T.; Pleschberger, M.; Susto, G. A.
An explainable artificial intelligence approach for unsupervised fault detection and diagnosis in rotating machinery
2022 Brito, L. C.; Susto, G. A.; Brito, J. N.; Duarte, M. A. V.
Anomaly Detection Approaches for Semiconductor Manufacturing
2017 Susto, Gian Antonio; Terzi, Matteo; Beghi, Alessandro
AutoSS: A Deep Learning-Based Soft Sensor for Handling Time-Series Input Data
2021 Bargellesi, N.; Beghi, A.; Rampazzo, M.; Susto, G. A.
Band Relevance Factor (BRF): A novel automatic frequency band selection method based on vibration analysis for rotating machinery
2024 Brito, L. C.; Susto, G. A.; Brito, J. N.; Duarte, M. A. V.