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Detection of spoiled meat using an electronic nose
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-0579-7181
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-3122-693X
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2014 (English)In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220Article in journal (Refereed) Submitted
Place, publisher, year, edition, pages
2014.
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-42942OAI: oai:DiVA.org:oru-42942DiVA: diva2:790663
Available from: 2015-02-25 Created: 2015-02-25 Last updated: 2017-12-04Bibliographically approved
In thesis
1. Modeling time-series with deep networks
Open this publication in new window or tab >>Modeling time-series with deep networks
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Örebro: Örebro university, 2014. 56 p.
Series
Örebro Studies in Technology, ISSN 1650-8580 ; 63
Keyword
multivariate time-series, deep learning, representation learning, unsupervised
National Category
Computer and Information Science
Research subject
Information technology
Identifiers
urn:nbn:se:oru:diva-39415 (URN)978-91-7529-054-6 (ISBN)
Public defence
2015-02-02, Hörsalen, Musikhögskolan, Örebro universitet, Fakultetsgatan 1, Örebro, 13:15 (English)
Opponent
Supervisors
Available from: 2014-12-08 Created: 2014-12-08 Last updated: 2017-10-17Bibliographically approved

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Längkvist, MartinLoutfi, Amy

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