Feb 26, 2021 · A novel framework, ie, “S-THAD”, is proposed for sensor-based temporal human activity detection from the continuous and untrimmed 3D motion sensor data.
A novel framework, i.e., “S-THAD”, is proposed for sensor-based temporal human activity detection from the continuous and untrimmed 3D motion sensor data, ...
Therefore, in this paper, a novel framework, i.e., “S-THAD”, is proposed for sensor-based temporal human activity detection from the continuous and untrimmed 3D ...
S-THAD: a framework for sensor-based temporal human activity detection from continuous data streams. https://doi.org/10.1007/s12652-021-02931-5 ·.
In this paper, we present and benchmark FilterNet, a flexible deep learning architecture for time series classification tasks, such as activity recognition via ...
[RDF data]. S-THAD: a framework for sensor-based temporal human activity detection from continuous data streams. Resource URI: https://dblp.l3s.de/d2r ...
S-THAD: a framework for sensor-based temporal human activity detection from continuous data streams ... Furthermore, a novel detection network is designed ...
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S-THAD: a framework for sensor-based temporal human activity detection from continuous data streams. Article 26 February 2021. Keywords. Support Vector Machine ...
S-THAD: a framework for sensor-based temporal human activity detection from continuous data streams. 2022, Journal of Ambient Intelligence and Humanized ...
S-THAD: a framework for sensor-based temporal human activity detection from continuous data streams ... Physical Activity Recognition Based on a Parallel ...