Yahaya, S.W. ORCID: 0000-0002-0394-6112, Langensiepen, C.
ORCID: 0000-0002-0165-9048 and Lotfi, A.
ORCID: 0000-0002-5139-6565,
2018.
Anomaly detection in activities of daily living using one-class support vector machine.
In: A. Lotfi, H. Bouchachia, A. Gegov, C. Langensiepen and M. McGinnity, eds.,
Advances in computational intelligence systems: contributions presented at the 18th UK Workshop on Computational Intelligence, September 5-7, 2018, Nottingham, UK.
Advances in intelligent systems and computing (AISC), 840
(840).
Cham, Switzerland: Springer, pp. 362-371.
ISBN 9783319979816
Item Type: | Chapter in book | ||||
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Description: | Paper presented at 18th UK Workshop on Computational Intelligence, Nottingham, 5-7 September 2018. | ||||
Creators: | Yahaya, S.W., Langensiepen, C. and Lotfi, A. | ||||
Publisher: | Springer | ||||
Place of Publication: | Cham, Switzerland | ||||
Date: | 12 August 2018 | ||||
Volume: | 840 | ||||
Number: | 840 | ||||
ISBN: | 9783319979816 | ||||
ISSN: | 2194-5357 | ||||
Identifiers: |
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Divisions: | Schools > School of Science and Technology | ||||
Record created by: | Jonathan Gallacher | ||||
Date Added: | 20 Aug 2018 10:45 | ||||
Last Modified: | 02 Feb 2023 13:50 | ||||
URI: | https://irep.ntu.ac.uk/id/eprint/34357 |
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