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Learning behavioral context recognition with multi-stream temporal convolutional networks
[article]
2018
arXiv
pre-print
Smart devices of everyday use (such as smartphones and wearables) are increasingly integrated with sensors that provide immense amounts of information about a person's daily life such as behavior and context. The automatic and unobtrusive sensing of behavioral context can help develop solutions for assisted living, fitness tracking, sleep monitoring, and several other fields. Towards addressing this issue, we raise the question: can a machine learn to recognize a diverse set of contexts and
arXiv:1808.08766v1
fatcat:bruvasyaonhudidp4czg5t4gf4