Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Frank Duckhorn"'
Publikováno v:
Applied Sciences, Vol 13, Iss 3, p 1670 (2023)
Softness is one of the essential properties of hygiene tissue products. Reliably measuring it is of utmost importance to ensure the balance between customer expectations and cost-effective tissue production. This study presents a method for assessing
Externí odkaz:
https://doaj.org/article/4f34aa3374a64b0c9df2597a2d1590ad
Autor:
Ruben Leithoff, Nikolas Dilger, Frank Duckhorn, Stefan Blume, Dario Lembcke, Constanze Tschöpe, Christoph Herrmann, Klaus Dröder
Publikováno v:
Batteries, Vol 7, Iss 1, p 19 (2021)
Due to the energy transition and the growth of electromobility, the demand for lithium-ion batteries has increased in recent years. Great demands are being placed on the quality of battery cells and their electrochemical properties. Therefore, the un
Externí odkaz:
https://doaj.org/article/d9d4a07cfd134352b0278d628076bbc9
Autor:
Ivan Kraljevski, Frank Duckhorn, Martin Barth, Constanze Tschoepe, Frank Schubert, Matthias Wolff
Publikováno v:
2021 IEEE Sensors.
Publikováno v:
Interspeech 2021.
We investigated and compared various algorithms in machine learning for anomaly assessment with different feature analyses on ultrasonic signals recorded by sensor networks. The following methods were used and compared in anomaly detection modeling:
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d3d0dde206bcc004bbcb5ae7e12084f8
https://publica.fraunhofer.de/handle/publica/266522
https://publica.fraunhofer.de/handle/publica/266522
Publikováno v:
2020 IEEE SENSORS.
We present a method for extracting health indicators from piezoelectric sensors applied in the case of microfluidic valves. Convolutional autoencoders were used to train a model on the normal operating conditions and tested on signals of different va
Autor:
Yong Chul Ju, Christian Richter, Matthias Wolff, Ivan Kraljevski, Frank Duckhorn, Constanze Tschoepe
Publikováno v:
I2MTC
In this study, we compare different machine learning approaches applied to acoustic resonance recognition of coins. Euro-cents and Euro-coins were classified by the sound emerging when throwing the coins onto a hard surface.The used dataset is a repr
Publikováno v:
IFIP Advances in Information and Communication Technology ISBN: 9783030491857
AIAI (2)
AIAI (2)
In this paper, acoustic resonance testing on glass intravenous (IV) bottles is presented. Different machine learning methods were applied to distinguish acoustic observations of bottles with defects from the intact ones. Due to the very limited amoun
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4d856bbe6f3f43d2e3328d69d0ad71e6
https://doi.org/10.1007/978-3-030-49186-4_17
https://doi.org/10.1007/978-3-030-49186-4_17
Autor:
Nikolas Dilger, Stefan Blume, Dario Lembcke, Constanze Tschöpe, Frank Duckhorn, Ruben Leithoff, Klaus Dröder, Christoph Herrmann
Publikováno v:
Batteries
Volume 7
Issue 1
Batteries 2021, 7 (1), 19; https://doi.org/10.3390/batteries7010019--http://www.mdpi.com/journal/batteries--http://www.bibliothek.uni-regensburg.de/ezeit/?2813972--2313-0105
Batteries, Vol 7, Iss 19, p 19 (2021)
Volume 7
Issue 1
Batteries 2021, 7 (1), 19; https://doi.org/10.3390/batteries7010019--http://www.mdpi.com/journal/batteries--http://www.bibliothek.uni-regensburg.de/ezeit/?2813972--2313-0105
Batteries, Vol 7, Iss 19, p 19 (2021)
Due to the energy transition and the growth of electromobility, the demand for lithium-ion batteries has increased in recent years. Great demands are being placed on the quality of battery cells and their electrochemical properties. Therefore, the un
Publikováno v:
AIP Conference Proceedings.
Machine learning (ML) methods and algorithms have been applied recently with great success in quality control and predictive maintenance. Its goal to build new and/or leverage existing algorithms to learn from training data and give accurate predicti