DanHAR: Dual Attention Network For Multimodal Human Activity Recognition Using Wearable Sensors

25 Jun 2020 Wenbin Gao Lei Zhang Qi Teng Hao Wu Fuhong Min Jun He

Human activity recognition (HAR) in ubiquitous computing has been beginning to incorporate attention into the context of deep neural networks (DNNs), in which the rich sensing data from multimodal sensors such as accelerometer and gyroscope is used to infer human activities. Recently, two attention methods are proposed via combining with Gated Recurrent Units (GRU) and Long Short-Term Memory (LSTM) network, which can capture the dependencies of sensing signals in both spatial and temporal domains simultaneously... (read more)

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