Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Ye, Juan; * | Callus, Elise
Affiliations: School of Computer Science, University of St Andrews, UK
Correspondence: [*] Corresponding author. E-mail: [email protected].
Abstract: Ambient Assisted Living (AAL) systems are increasingly being deployed in real-world environments and for long periods of time. This significantly challenges current approaches that require substantial setup investment and cannot account for frequent, unpredictable changes in human behaviours, health conditions, and sensor deployments. The state-of-the-art methodology in studying human activity recognition is cultivated from short-term lab or testbed experimentation, i.e., relying on well-annotated sensor data and assuming no change in activity models. This paper propose a technique, EMILEA, to evolve an activity model over time with new types of activities. This technique novelly integrates two recent advances in continual learning: Net2Net – expanding the architecture of a model while transferring the knowledge from the previous model to the new model and Gradient Episodic Memory – controlling the update on the model parameters to maintain the performance on recognising previously learnt activities. This technique has been evaluated on two real-world, third-party, datasets and demonstrated promising results on enhancing the learning capacity to accommodate new activities that are incrementally introduced to the model while not compromising the accuracy on old activities.
Keywords: Activity recognition, continual learning, smart home
DOI: 10.3233/AIS-200566
Journal: Journal of Ambient Intelligence and Smart Environments, vol. 12, no. 4, pp. 313-325, 2020
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]