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1 Ergebnisse
1
A Sparse Autoencoder Based Adversarial Open Set Domain Adap..:
, In:
2022 International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD)
,
Liu, Zhao-Hua
;
Jiang, Lin-Bo
;
Wei, Hua-Liang
... - p. 1-6 , 2022
Link:
https://doi.org/10.1109/ICSMD57530.2022.10058385
RT T1 <cTitle>2022 International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD)</cTitle>: T1 <Title>A Sparse Autoencoder Based Adversarial Open Set Domain Adaptation Model for Fault Diagnosis of Rotating Machinery</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10058385&Exemplar=1&LAN=DE A1 Liu, Zhao-Hua A1 Jiang, Lin-Bo A1 Wei, Hua-Liang A1 Wang, Chang-Tong A1 Lv, Ming-Yang A1 Chen, Lei YR 2022 K1 Fault diagnosis K1 Employee welfare K1 Training K1 Adaptation models K1 Data analysis K1 Target recognition K1 Adversarial machine learning K1 adversarial learning K1 deep learning K1 domain adaptation K1 fault diagnosis K1 open set recognition K1 rotating machinery K1 unknown faults K1 sparse autoencoder SP 1 OP 6 LK http://dx.doi.org/https://doi.org/10.1109/ICSMD57530.2022.10058385 DO https://doi.org/10.1109/ICSMD57530.2022.10058385 SF ELIB - SuUB Bremen
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