SENSOR-BASED HUMAN ACTIVITY RECOGNITION USING BIDIRECTIONAL LSTM FOR CLOSELY RELATED ACTIVITIES

SENSOR-BASED HUMAN ACTIVITY RECOGNITION USING BIDIRECTIONAL LSTM FOR CLOSELY RELATED ACTIVITIES

Recognizing human activities using deep learning methods has significance in many fields such as sports, motion tracking, surveillance, healthcare and robotics. Inertial sensors comprising of accelerometers and gyroscopes are commonly used for sensor based HAR. In this study, a Bidirectional Long Sh...

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Bibliographic Details
Main Author:	Pavai, Arumugam Thendramil
Format:	Others
Published:	CSUSB ScholarWorks 2018
Subjects:	deep learning inertial sensors human activity recognition bidirectional long short-term memory Artificial Intelligence and Robotics Computer Engineering Computer Sciences
Online Access:	https://scholarworks.lib.csusb.edu/etd/776 https://scholarworks.lib.csusb.edu/cgi/viewcontent.cgi?article=1864&context=etd

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