A Framework of Combining Short-Term Spatial/Frequency Feature Extraction and Long-Term IndRNN for Activity Recognition †

@article{Zhao2020AFO,
  title={A Framework of Combining Short-Term Spatial/Frequency Feature Extraction and Long-Term IndRNN for Activity Recognition †},
  author={Beidi Zhao and Shuai Li and Yanbo Gao and Chuankun Li and Wanqing Li},
  journal={Sensors (Basel, Switzerland)},
  year={2020},
  volume={20}
}
Smartphone-sensors-based human activity recognition is attracting increasing interest due to the popularization of smartphones. It is a difficult long-range temporal recognition problem, especially with large intraclass distances such as carrying smartphones at different locations and small interclass distances such as taking a train or subway. To address this problem, we propose a new framework of combining short-term spatial/frequency feature extraction and a long-term independently recurrent… 

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