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Activity recognition using semi-Markov models on real world smart home datasets

Year: 2010

Type: article

Abstract: Accurately recognizing human activities from sensor data recorded in a smart home setting is a challenging task. Typically, probabilistic models such as the hidden Markov model (HMM) or conditional random fields (CRF) are used to map the observed sen

Source: Journal of Ambient Intelligence and Smart Environments

DOI: 10.3233/ais-2010-0070

Authors: T.L.M. van Kasteren, G. Englebienne, B.J.A. Kröse

Institution: University of Amsterdam

Language: English

Topic: Context-Aware Activity Recognition Systems

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W2126484555

FWCI: 7.273

Cites: 33

Cited by: 136

Related to: 10