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• W2811346987 abstract "In this paper, we address the issue of indoor activities of daily living recognition with a novel Activity Recognition System (ARS). This system only uses interactions between objects. Their locations is provided by a tracking system based on passive RFID tags to compute activity probabilities. Classification within the tracking system is done through a random forest that gives over 97% in accuracy. Activities are represented by the use of a custom behaviour tree, which makes it possible to compose interactions to form activities of any complexity. Interactions and activities are defined in a human readable form to allow everyone to expand them with minimal prior knowledge." @default.
• W2811346987 created "2018-07-10" @default.
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• W2811346987 date "2017-08-01" @default.
• W2811346987 modified "2023-10-13" @default.
• W2811346987 title "RFID based activities of daily living recognition" @default.
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• W2811346987 doi "https://doi.org/10.1109/uic-atc.2017.8397548" @default.
• W2811346987 hasPublicationYear "2017" @default.
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