Combining Residual and LSTM Recurrent Networks for Transportation Mode Detection Using Multimodal Sensors Integrated in Smartphones

In recent years, with the rapid development of public transportation, the ways people travel has become more diversified and complicated. Transportation mode detection, as a significant branch of human activity recognition (HAR), is of great importance in analyzing human travel patterns, traffic pre...

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Veröffentlicht in:	IEEE transactions on intelligent transportation systems Jg. 22; H. 9; S. 5473 - 5485
Hauptverfasser:	Wang, Chenxing, Luo, Haiyong, Zhao, Fang, Qin, Yanjun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.09.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy activity recognition Algorithms Context awareness Feature extraction Global Positioning System Human activity recognition Intelligent sensors Machine learning Moving object recognition multimodal sensors Public transportation Sensors Smart phones Smartphones Traffic planning transportation pattern recognition Travel patterns Weight reduction
ISSN:	1524-9050, 1558-0016
Online-Zugang:	Volltext
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