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Gabriel Michau
Gabriel Michau
Tean Leader - New Maintenance Technologies, Stadler Service AG
Bestätigte E-Mail-Adresse bei ethz.ch
Titel
Zitiert von
Zitiert von
Jahr
Domain adaptive transfer learning for fault diagnosis
Q Wang, G Michau, O Fink
2019 Prognostics and System Health Management Conference (PHM-Paris), 279-285, 2019
1572019
Unsupervised transfer learning for anomaly detection: Application to complementary operating condition transfer
G Michau, O Fink
Knowledge-Based Systems 216, 106816, 2021
1262021
Temporal signals to images: Monitoring the condition of industrial assets with deep learning image processing algorithms
GR Garcia, G Michau, M Ducoffe, JS Gupta, O Fink
Proceedings of the Institution of Mechanical Engineers, Part O: Journal of …, 2022
912022
Fully Learnable Deep Wavelet Transform for Unsupervised Monitoring of High-Frequency Time Series
G Michau, O Fink
arXiv preprint arXiv:2105.00899, 2021
782021
Feature learning for fault detection in high-dimensional condition-monitoring signals
G Michau, Y Hu, T Palmé, O Fink
Proceedings of the Institution of Mechanical Engineers, Part O: Journal of …, 2019
732019
Missing-class-robust domain adaptation by unilateral alignment
Q Wang, G Michau, O Fink
IEEE Transactions on Industrial Electronics 68 (1), 663-671, 2020
692020
Bluetooth Data in an Urban Context: Retrieving Vehicle Trajectories
G Michau, A Nantes, A Bhaskar, E Chung, P Abry, P Borgnat
IEEE Transactions on Intelligent Transportation Systems 18 (9), 2377-2386, 2017
672017
A primal-dual algorithm for link dependent origin destination matrix estimation
G Michau, N Pustelnik, P Borgnat, P Abry, A Nantes, A Bhaskar, E Chung
IEEE Transactions on Signal and Information Processing over Networks 3 (1 …, 2016
432016
Domain Adaptation for One-Class Classification: Monitoring the Health of Critical Systems Under Limited Information
G Michau, O Fink
International Journal of Prognostics and Health Management 10 (028), 11, 2019
382019
Contrastive Learning for Fault Detection and Diagnostics in the Context of Changing Operating Conditions and Novel Fault Types
K Rombach, G Michau, O Fink
Sensors 21 (10), 3550, 2021
372021
Controlled generation of unseen faults for Partial and Open-Partial domain adaptation
K Rombach, G Michau, O Fink
Reliability Engineering & System Safety 230, 108857, 2023
362023
Deep Feature Learning Network for Fault Detection and Isolation
G Michau, T Palmé, O Fink
Annual Conference of the Prognostics and Health Management Society 2017 …, 2017
332017
Unsupervised Fault Detection in Varying Operating Conditions
G Michau, O Fink
arXiv preprint arXiv:1907.06481, 2019
322019
Interpretable Detection of Partial Discharge in Power Lines with Deep Learning
G Michau, CC Hsu, O Fink
Sensors 21 (6), 2154, 2021
312021
Decision Support System for an Intelligent Operator of Utility Tunnel Boring Machines
G Rodriguez Garcia, G Michau, HH Einstein, O Fink
arXiv e-prints, arXiv: 2101.02463, 2021
31*2021
Fleet PHM for Critical Systems: Bi-level Deep Learning Approach for Fault Detection
G Michau, T Palmé, O Fink
PHM Society European Conference 4 (1), 2018
312018
Retrieving dynamic origin-destination matrices from Bluetooth data
G Michau, A Nantes, E Chung, P Abry, P Borgnat
Transportation Research Board (TRB) 93rd Annual Meeting Compendium of Papers …, 2014
182014
Combining traffic counts and Bluetooth data for link-origin-destination matrix estimation in large urban networks: The Brisbane case study
G Michau, N Pustelnik, P Borgnat, P Abry, A Bhaskar, E Chung
arxiv, 2017
152017
Estimating link-dependent origin-destination matrices from sample trajectories and traffic counts
G Michau, P Borgnat, N Pustelnik, P Abry, A Nantes, E Chung
2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015
142015
Canonical polyadic decomposition and deep learning for machine fault detection
G Frusque, M Gabriel, F Olga
PHM Society European Conference 6 (1), 9-9, 2021
102021
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