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Sensor-based human activity recognition aims at detecting various physical activities performed by people with ubiquitous sensors. Different from existing deep learning-based method which mainly extracting black-box features from the raw sensor data, we propose a hierarchical multi-view aggregation network based on multi-view feature spaces. Specifically, we first construct various views of feature spaces for each individual sensor in terms of white-box features and black-box features. Then our model learns a unified representation for multi-view features by aggregating views in a hierarchical context from the aspect of feature level, position level and modality level. We design three aggregation modules corresponding to each level aggregation respectively. Based on the idea of non-local operation and attention, our fusion method is able to capture the correlation between features and leverage the relationship across different sensor position and modality. We comprehensively evaluate our method on 12 human activity benchmark datasets and the resulting accuracy outperforms the state-of-the-art approaches.
This article was published in the following journal.
Name: PloS one
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A view of the world and the individual's environment as comprehensible, manageable, and meaningful, claiming that the way people view their life has a positive influence on their health.
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A multi- and interdisciplinary field concerned with improving health and achieving equity in health for all people. It transcends national boundaries, promotes cooperation and collaboration within and beyond health science fields, and combines population-based disease prevention with individually-based patient care.
A broad category of multi-ingredient preparations that are marketed for the relief of upper respiratory symptoms resulting from the COMMON COLD; ALLERGIES; or HUMAN INFLUENZA. While the majority of these medications are available as OVER-THE-COUNTER DRUGS some of them contain ingredients that require them to be sold as PRESCRIPTION DRUGS or as BEHIND-THE COUNTER DRUGS.
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