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Deep learning approaches emphasized on learning spatio-temporal features for action recognition. Different to previous works, we separate the spatio-temporal feature learning unity into the spatial feature learning and the spatial/temporal feature pooling procedures. Using the temporal slowness regularized independent subspace analysis network, we learn(More)
Human action recognition plays an important role in E-health, such as risk assessment, disease treatment, rehabilitation and so on. We proposes a mobile phone-based internet of things method for human action recognition. In the work, data are collected from a smart phone worn on the waist and transmitted to the application server on the internet. The(More)
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