Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Bernd Zimmering"'
Autor:
Bernd Zimmering, Oliver Niggemann, Constanze Hasterok, Erik Pfannstiel, Dario Ramming, Julius Pfrommer
Publikováno v:
Sensors, Vol 21, Iss 7, p 2397 (2021)
In the field of Cyber-Physical Systems (CPS), there is a large number of machine learning methods, and their intrinsic hyper-parameters are hugely varied. Since no agreed-on datasets for CPS exist, developers of new algorithms are forced to define th
Externí odkaz:
https://doaj.org/article/55b6178217dc4a6abab26996eefe2e64
Publikováno v:
atp magazin. 63:78-84
Machine Learning methods have achieved some impressive results over the past decade. However, this success was in large part a result of utilizing large amounts of data and growing computational resources efficiently. To extend this recent success to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b0c9d7374a03f6758239aa342658ed86
https://doi.org/10.17560/atp.v63i9.2600
https://doi.org/10.17560/atp.v63i9.2600
Autor:
Oliver Niggemann, Bernd Zimmering, Henrik Steude, Jan Lukas Augustin, Alexander Windmann, Samim Multaheb
Publikováno v:
Digital Transformation ISBN: 9783662650035
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2f14ff0870d2c3d2b459139ec16c0c91
https://doi.org/10.1007/978-3-662-65004-2_17
https://doi.org/10.1007/978-3-662-65004-2_17
Publikováno v:
at - Automatisierungstechnik. 69:221-230
The application of machine learning, especially of trained neural networks, requires a high level of trust in their results. A key to this trust is the network’s ability to assess the uncertainty of the computed results. This is a prerequisite for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1363e5a5d76f8068c5df842c4a0f255b
https://doi.org/10.1515/auto-2020-0122
https://doi.org/10.1515/auto-2020-0122
Publikováno v:
2022 IEEE 5th International Conference on Industrial Cyber-Physical Systems (ICPS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::55d53c02282827bb1487430ebf32f46d
https://doi.org/10.1109/icps51978.2022.9816908
https://doi.org/10.1109/icps51978.2022.9816908