Anomaly detection in activities of daily living using one-class support vector machine

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

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Item Type:	Chapter in book
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:	Number Type 10.1007/978-3-319-97982-3_30 DOI
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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