Machine Learning in Human Activity Recognition

in Special Issue   Posted on April 29, 2021 

Information for the Special Issue

Submission Deadline: Mon 31 Jan 2022
Journal Impact Factor : 3.275
Journal Name : Sensors
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Special Issue Call for Papers:

Dear Colleagues,

Human Activity Recognition (HAR) using pervasive and body-worn sensors has become a major research field with numerous practical applications. At the heart of most HAR systems lies the automated analysis of sensor readings, for which machine learning techniques are typically applied. With the explosion of research in the core machine learning area, numerous methods have been developed that are also of value for the HAR community. However, HAR comes with its own challenges for machine learning methods, such as challenging data quality, including sensor noise, faulty sensor readings, or ambiguities; often only very small datasets come with ground truth annotation; computational challenges for performing activity recognition in real time and on severely resource constrained devices; open ended activity recognition; and continuous adaptation of recognition systems, to name but a few. This Special Issue aims to provide an overview of the state-of-the-art and latest developments in the field of machine learning for human activity recognition.

Prof. Dr. Thomas Ploetz
Dr. Yu Guan
Prof. Dr. Daniel Roggen
Guest Editors

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