Items where Author is "Yahaya, SW"
Journal article
YAHAYA, S.W., LOTFI, A. and MAHMUD, M., 2021. Towards a data-driven adaptive anomaly detection system for human activity. Pattern Recognition Letters, 145, pp. 200-207. ISSN 0167-8655
YAHAYA, S.W., LOTFI, A. and MAHMUD, M., 2021. Detecting anomaly and its sources in activities of daily living. SN Computer Science, 2 (1): 14. ISSN 2661-8907
YAHAYA, S.W., LOTFI, A. and MAHMUD, M., 2019. A consensus novelty detection ensemble approach for anomaly detection in activities of daily living. Applied Soft Computing, 83: 105613. ISSN 1568-4946
LOTFI, A., LANGENSIEPEN, C. and YAHAYA, S.W., 2018. Socially assistive robotics: robot exercise trainer for older adults. Technologies, 6 (1): 32. ISSN 2227-7080
Chapter in book
BORALESSA, K., IHIANLE, I.K., MACHADO, P., YAHAYA, S.W. and LOTFI, A., 2024. Input-adaptation approach for human activity recognition. In: PETRA '24: proceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments. New York City: ACM, 369 - 374. ISBN 9798400717604
ADAMA, D.A., OLATUNJI, T.Y., YAHAYA, S.W. and LOTFI, A., 2021. Comparative analysis of K-means and traversal optimisation algorithms. In: T. JANSEN, R. JENSEN, N. MAC PARTHALÁIN and C.-M. LIN, eds., Advances in computational intelligence systems: contributions presented at the 20th UK Workshop on Computational Intelligence, September 8-10, 2021, Aberystwyth, Wales, UK. Advances in intelligent systems and computing book series (1409). Cham: Springer, pp. 300-311. ISBN 9783030870935
YAHAYA, S.W., LOTFI, A., MAHMUD, M. and ADAMA, D.A., 2021. A centralised cloud-based monitoring system for older adults in a community. In: 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC) [proceedings]. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), pp. 2439-2443. ISBN 9781665442077
YAHAYA, S.W., LOTFI, A. and MAHMUD, M., 2020. Towards the development of an adaptive system for detecting anomaly in human activities. In: 2020 IEEE Symposium Series on Computational Intelligence (SSCI) proceedings. Institute of Electrical and Electronics Engineers (IEEE), pp. 534-541. ISBN 9781728125473
YAHAYA, S.W., LOTFI, A., MAHMUD, M., MACHADO, P. and KUBOTA, N., 2020. Gesture recognition intermediary robot for abnormality detection in human activities. In: 2019 IEEE Symposium Series on Computational Intelligence (SSCI). Institute of Electrical and Electronics Engineers (IEEE), pp. 1415-1421. ISBN 9781728124865
ANDEREZ, D.O., DOS SANTOS, L.P., LOTFI, A. and YAHAYA, S.W., 2019. Accelerometer-based hand gesture recognition for human-robot interaction. In: 2019 IEEE Symposium Series on Computational Intelligence (SSCI), Xiamen, China, 6-9 December 2019. Institute of Electrical and Electronics Engineers (IEEE), pp. 1402-1406. ISBN 9781728124858
YAHAYA, S.W., LOTFI, A. and MAHMUD, M., 2019. A framework for anomaly detection in activities of daily living using an assistive robot. In: Proceedings of the 2nd UK-RAS Robotics and Autonomous Systems Conference, Loughborough, 24 January 2019. London: UK-RAS Network, pp. 131-134.
YAHAYA, S.W., LOTFI, A. and MAHMUD, M., 2019. A similarity measure approach for identifying causes of anomaly in activities of daily living. In: Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments - PETRA '19, Rhodes, Greece, 5-7 June 2019. New York: ACM, pp. 575-579. ISBN 9781450362320
YAHAYA, S.W., LANGENSIEPEN, C. and LOTFI, A., 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
Thesis
YAHAYA, S.W., 2021. User-centric anomaly detection in activities of daily living. PhD, Nottingham Trent University.