Towards improving feature extraction and classification for activity recognition on streaming data

Volume: 8, Issue: 2, Pages: 177 - 189
Published: Sep 24, 2016
Abstract
An activity recognition system on streaming data must analyze the drift in the sensing values and, at any significant change detected, decide if there is a change in the activity performed by the person. The performances of such system depend on both the feature extraction (FE) and the classification stages in the context of streaming data. In the context of streaming and high imbalanced data, this paper proposes and evaluates three FE methods...
Paper Details
Title
Towards improving feature extraction and classification for activity recognition on streaming data
Published Date
Sep 24, 2016
Volume
8
Issue
2
Pages
177 - 189
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