Ensemble classifier of long short-term memory with fuzzy temporal windows on binary sensors for activity recognition

作者：

Highlights：

• We propose a representation based on Fuzzy Temporal Windows for binary-sensors.

• Long Short-Term Memory is deployed as a means of sequence classifier.

• A balanced training is included to build an ensemble of activity-based classifiers.

• The proposed approach is evaluated and benchmarked against previous approaches.

摘要

•We propose a representation based on Fuzzy Temporal Windows for binary-sensors.•Long Short-Term Memory is deployed as a means of sequence classifier.•A balanced training is included to build an ensemble of activity-based classifiers.•The proposed approach is evaluated and benchmarked against previous approaches.

论文关键词：Activity recognition,Fuzzy temporal windows,Long short-term memory,Unbalanced data,Ensemble architectures

论文评审过程：Received 11 January 2018, Revised 28 July 2018, Accepted 29 July 2018, Available online 1 August 2018, Version of Record 9 August 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.07.068