Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery

3 Mar 2020Zepeng HuoArash PakBinXiaohan ChenNathan HurleyYe YuanXiaoning QianZhangyang WangShuai HuangBobak Mortazavi

Activity recognition in wearable computing faces two key challenges: i) activity characteristics may be context-dependent and change under different contexts or situations; ii) unknown contexts and activities may occur from time to time, requiring flexibility and adaptability of the algorithm. We develop a context-aware mixture of deep models termed the {\alpha}-\b{eta} network coupled with uncertainty quantification (UQ) based upon maximum entropy to enhance human activity recognition performance... (read more)

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