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Publications Lists     [ all BibTeX ]  

Publications of keyword: Deep Learning
M. Maggipinto, M. Terzi, G.A. Susto. IntroVAC: Introspective Variational Classifiers for Learning Interpretable Latent Subspaces. Engineering Applications of Artificial Intelligence, vol. 109, 2022    [ abstract ] [url] [BibTeX]  
M. Terzi, A. Achille, M. Maggipinto, G.A. Susto. Adversarial Training Reduces Information and Improves Transferability. 35th AAAI Conference on Artificial Intelligence, (arXiv:2007.11259), 2021    [ abstract ] [url] [BibTeX]  
R. Fantinel, A. Cenedese, G. Fadel. Hybrid Learning Driven by Dynamic Descriptors for Video Classification of Reflective Surfaces. IEEE Transactions on Industrial Informatics, vol. 17(12), pp. 8102--8111, 2021    [ abstract ] [url] [BibTeX]  
D. Tosato, D. Dalle Pezze, C. Masiero, G.A. Susto, A. Beghi. Alarm Logs in Packaging Industry (ALPI). IEEEDataPort, 2020    [ abstract ] [url] [BibTeX]  
M. Maggipinto, M. Terzi, G.A. Susto. Beta-Variational Classifiers Under Attack. IFAC World Congress, 2020   [BibTeX]  
M. Terzi, G.A. Susto, P. Chaudhari. Directional Adversarial Training for Cost Sensitive Deep Learning Classification Applications. Engineering Applications of Artificial Intelligence, vol. 91, 2020    [ abstract ] [url] [BibTeX]  
N. Gentner, M. Carletti, G.A. Susto, A. Kyek, Y. Yang. Enhancing Scalability of Virtual Metrology: a Deep Learning-based Approach for Domain Adaptation. Winter Simulation Conference, 2020    [ abstract ] [BibTeX]  
R. Fantinel, A. Cenedese. Multistep hybrid learning: CNN driven by spatial–temporal features for faults detection on metallic surfaces. Journal of Electronic Imaging, vol. 4, pp. 29, 2020    [ abstract ] [url] [BibTeX]  
T. Barbariol, D. Masiero, E. Feltresi, G.A. Susto. Time series Forecasting to detect anomalous behaviours in Multiphase Flow Meter. North Sea Flow Measurement Workshop, 2020   [BibTeX]  
M. Carletti, C. Masiero, A. Beghi, G.A. Susto. A deep learning approach for anomaly detection with industrial time series data: a refrigerators manufacturing case study. Procedia Manufacturing, vol. 38, pp. 233-240, 2019    [ abstract ] [url] [BibTeX]  
L. Brunelli, C. Masiero, D. Tosato, A. Beghi, G.A. Susto. Deep Learning-based Production Forecasting in Manufacturing: a Packaging Equipment Case Study. Procedia Manufacturing, vol. 38, pp. 248-255, 2019    [ abstract ] [BibTeX]  
M. Terzi, C. Masiero, A. Beghi, M. Maggipinto, G.A. Susto. Deep Learning for Virtual Metrology: Modeling with Optical Emission Spectroscopy Data. IEEE 3rd International Forum on Research and Technologies for Society and Industry (RTSI), 2017    [ abstract ] [url] [BibTeX]