New Sensor Data Structuring for Deeper Feature Extraction in Human Activity Recognition

New Sensor Data Structuring for Deeper Feature Extraction in Human Activity Recognition

For the effective application of thriving human-assistive technologies in healthcare services and human–robot collaborative tasks, computing devices must be aware of human movements. Developing a reliable real-time activity recognition method for the continuous and smooth operation of such smart dev...

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Bibliographic Details
Main Authors:	Tsige Tadesse Alemayoh, Jae Hoon Lee, Shingo Okamoto
Format:	Article
Language:	English
Published:	MDPI AG 2021-04-01
Series:	Sensors
Subjects:	human activity recognition inertial measurement unit sensors deep learning convolutional neural network input adaptation
Online Access:	https://www.mdpi.com/1424-8220/21/8/2814

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