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SynDAB-Leitfaden_GenerierungNutzungSynDatenV7.pdf
SynDAB-Leitfaden_GenerierungNutzungSynDatenV7.pdf
Jan 23, 2024 - SynDAB Dataset
Adobe PDF - 294.3 KB - MD5: 7900501cb72c18abd4181cfe6dd8642b
SynDAB(Universität Stuttgart)
Dec 26, 2023
Stuttgart Open Relay Degradation Dataset (SOReDD)
Stuttgart Open Relay Degradation Dataset (SOReDD)
Apr 1, 2022
Maschler, Benjamin; Iliev, Angel; Pham, Thi Thu Huong; Weyrich, Michael, 2022, "Stuttgart Open Relay Degradation Dataset (SOReDD)", https://doi.org/10.18419/DARUS-2785, DaRUS, V1
Real-life industrial use cases for machine learning oftentimes involve heterogeneous and dynamic assets, processes and data, resulting in a need to continuously adapt the learning algorithm accordingly. Industrial transfer learning offers to lower the effort of such adaptation by allowing the utilization of previously acquired knowledge in solving...
2022 Stuttgart Open Relay Degradation Dataset (SOReDD).pdf
2022 Stuttgart Open Relay Degradation Dataset (SOReDD).pdf
Apr 1, 2022 - Stuttgart Open Relay Degradation Dataset (SOReDD)
Adobe PDF - 968.8 KB - MD5: 61398d524b1f3f5b6fcd7e1f5e30c61a
Read Me
A13.json
Apr 1, 2022 - Stuttgart Open Relay Degradation Dataset (SOReDD)
JSON - 98.5 MB - MD5: e1c48f682cf59d819aef21e1b4180f5b
A1.json
Apr 1, 2022 - Stuttgart Open Relay Degradation Dataset (SOReDD)
JSON - 426.0 KB - MD5: 22bf59a4d72a67b9ef59a30aa708f352
A2.json
Apr 1, 2022 - Stuttgart Open Relay Degradation Dataset (SOReDD)
JSON - 64.4 MB - MD5: 14d7cbd6d32a5b5d705297922b083bdd
A984.json
Apr 1, 2022 - Stuttgart Open Relay Degradation Dataset (SOReDD)
JSON - 8.6 MB - MD5: d25f3314a42f8890ef059c6c1b8f0240
A985.json
Apr 1, 2022 - Stuttgart Open Relay Degradation Dataset (SOReDD)
JSON - 5.9 MB - MD5: 9aa1c454567685dbe6195d130b9114f8
A986.json
Apr 1, 2022 - Stuttgart Open Relay Degradation Dataset (SOReDD)
JSON - 17.1 MB - MD5: a46e7d09e7328777e9c20eac479a7f2b
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