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Hidden dimensions of the data: PCA vs autoencoders
Cacciarelli, Davide
Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark; Department of Mathematical Sciences, Norwegian University of Science and Technology, Trondheim, Norway.
Kulahci, Murat
Luleå University of Technology, Department of Social Sciences, Technology and Arts, Business Administration and Industrial Engineering. Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark.
ORCID iD:
0000-0003-4222-9631
2023 (English)
In:
Quality Engineering, ISSN 0898-2112, E-ISSN 1532-4222, Vol. 35, no 4, p. 741-750
Article in journal (Refereed) Published
Place, publisher, year, edition, pages
Taylor & Francis, 2023. Vol. 35, no 4, p. 741-750
National Category
Computer Sciences
Research subject
Quality Technology and Logistics
Identifiers
URN:
urn:nbn:se:ltu:diva-99664
DOI:
10.1080/08982112.2023.2231064
ISI:
001040916100001
Scopus ID:
2-s2.0-85166669210
OAI: oai:DiVA.org:ltu-99664
DiVA, id:
diva2:1787849
Note
Validerad;2023;Nivå 2;2023-11-09 (hanlid)
Available from:
2023-08-15
Created:
2023-08-15
Last updated:
2024-03-07
Bibliographically approved
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modern-language-association-8th-edition
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