Knowledge Incorporation for Machine Learning in Condition Monitoring: A Survey

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Standard

Knowledge Incorporation for Machine Learning in Condition Monitoring: A Survey. / Hagendorfer, Elias Jan.
Proceedings - 2021 International Symposium on Electrical, Electronics and Information Engineering, ISEEIE 2021. Association for Computing Machinery (ACM), 2021. p. 230-240 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Harvard

Hagendorfer, EJ 2021, Knowledge Incorporation for Machine Learning in Condition Monitoring: A Survey. in Proceedings - 2021 International Symposium on Electrical, Electronics and Information Engineering, ISEEIE 2021. ACM International Conference Proceeding Series, Association for Computing Machinery (ACM), pp. 230-240, 2021 International Symposium on Electrical, Electronics and Information Engineering, ISEEIE 2021, Virtual, Online, Korea, Republic of, 19/02/21. https://doi.org/10.1145/3459104.3459144

APA

Hagendorfer, E. J. (2021). Knowledge Incorporation for Machine Learning in Condition Monitoring: A Survey. In Proceedings - 2021 International Symposium on Electrical, Electronics and Information Engineering, ISEEIE 2021 (pp. 230-240). (ACM International Conference Proceeding Series). Association for Computing Machinery (ACM). https://doi.org/10.1145/3459104.3459144

Vancouver

Hagendorfer EJ. Knowledge Incorporation for Machine Learning in Condition Monitoring: A Survey. In Proceedings - 2021 International Symposium on Electrical, Electronics and Information Engineering, ISEEIE 2021. Association for Computing Machinery (ACM). 2021. p. 230-240. (ACM International Conference Proceeding Series). doi: 10.1145/3459104.3459144

Author

Hagendorfer, Elias Jan. / Knowledge Incorporation for Machine Learning in Condition Monitoring : A Survey. Proceedings - 2021 International Symposium on Electrical, Electronics and Information Engineering, ISEEIE 2021. Association for Computing Machinery (ACM), 2021. pp. 230-240 (ACM International Conference Proceeding Series).

Bibtex - Download

@inproceedings{781900a1e8ae40629808902208d87cd9,
title = "Knowledge Incorporation for Machine Learning in Condition Monitoring: A Survey",
author = "Hagendorfer, {Elias Jan}",
note = "Publisher Copyright: {\textcopyright} 2021 ACM.; 2021 International Symposium on Electrical, Electronics and Information Engineering, ISEEIE 2021 ; Conference date: 19-02-2021 Through 21-02-2021",
year = "2021",
month = feb,
day = "19",
doi = "10.1145/3459104.3459144",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery (ACM)",
pages = "230--240",
booktitle = "Proceedings - 2021 International Symposium on Electrical, Electronics and Information Engineering, ISEEIE 2021",
address = "United States",

}

RIS (suitable for import to EndNote) - Download

TY - GEN

T1 - Knowledge Incorporation for Machine Learning in Condition Monitoring

T2 - 2021 International Symposium on Electrical, Electronics and Information Engineering, ISEEIE 2021

AU - Hagendorfer, Elias Jan

N1 - Publisher Copyright: © 2021 ACM.

PY - 2021/2/19

Y1 - 2021/2/19

UR - http://www.scopus.com/inward/record.url?scp=85113229418&partnerID=8YFLogxK

U2 - 10.1145/3459104.3459144

DO - 10.1145/3459104.3459144

M3 - Conference contribution

AN - SCOPUS:85113229418

T3 - ACM International Conference Proceeding Series

SP - 230

EP - 240

BT - Proceedings - 2021 International Symposium on Electrical, Electronics and Information Engineering, ISEEIE 2021

PB - Association for Computing Machinery (ACM)

Y2 - 19 February 2021 through 21 February 2021

ER -

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