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1
Remaining Useful Life Estimation with End-to-end Learning f..:
, In:
2022 61st Annual Conference of the Society of Instrument and Control Engineers (SICE)
,
Natsumeda, Masanao
- p. 542-547 , 2022
Link:
https://doi.org/10.23919/SICE56594.2022.9905797
RT T1 <cTitle>2022 61st Annual Conference of the Society of Instrument and Control Engineers (SICE)</cTitle>: T1 <Title>Remaining Useful Life Estimation with End-to-end Learning from Long Run-to-failure Data</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9905797&Exemplar=1&LAN=DE A1 Natsumeda, Masanao YR 2022 K1 Degradation K1 Instruments K1 Computational modeling K1 NASA K1 Life estimation K1 Semisupervised learning K1 Benchmark testing K1 Remaining useful life estimation K1 deep learning K1 sequential model SP 542 OP 547 LK http://dx.doi.org/https://doi.org/10.23919/SICE56594.2022.9905797 DO https://doi.org/10.23919/SICE56594.2022.9905797 SF ELIB - SuUB Bremen
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