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/Author (Javier Medina Quero, Claire Orr, Shuai Zang, Chris Nugent, Alberto Salguero and Macarena Espinilla)
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/Subject (In this paper, we present a methodology for Real-Time Activity Recognition of Interleaved Activities based on Fuzzy Logic and Recurrent Neural Networks. Firstly, we propose a representation of binary-sensor activations based on multiple Fuzzy Temporal Windows. Second, an ensemble of activity-based classifiers for balanced training and selection of relevant sensor is proposed. Each classifier is configured as a Long Short-Term Memory with self-reliant detection of interleaved activities. The proposed approach was evaluated using well-known interleaved binary-sensor datasets comprised of activities of daily living.)
/Title (Real-time Recognition of Interleaved Activities based on Ensemble classifier of Long Short-Term Memory with Fuzzy Temporal Windows)
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Javier Medina Quero, Claire Orr, Shuai Zang, Chris Nugent, Alberto Salguero and Macarena Espinilla
In this paper, we present a methodology for Real-Time Activity Recognition of Interleaved Activities based on Fuzzy Logic and Recurrent Neural Networks. Firstly, we propose a representation of binary-sensor activations based on multiple Fuzzy Temporal Windows. Second, an ensemble of activity-based classifiers for balanced training and selection of relevant sensor is proposed. Each classifier is configured as a Long Short-Term Memory with self-reliant detection of interleaved activities. The proposed approach was evaluated using well-known interleaved binary-sensor datasets comprised of activities of daily living.
Real-time Recognition of Interleaved Activities based on Ensemble classifier of Long Short-Term Memory with Fuzzy Temporal Windows
2018-06-01T14:54:06Z
LaTeX with hyperref package
2018-09-25T15:30:06+01:00
2018-09-25T15:30:06+01:00
Real-Time Activity Recognition ; Interleaved Activities ; Fuzzy Temporal Windows ; Long Short-Term Memory
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