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Found 3 papers, 1 papers with code
A Comprehensive Review of Automated Data Annotation Techniques in Human Activity Recognition
Human Activity Recognition (HAR) has become one of the leading research topics of the last decade.
Estimating indoor occupancy through low-cost BLE devices
Detecting the presence of persons and estimating their quantity in an indoor environment has grown in importance recently.
B-HAR: an open-source baseline framework for in depth study of human activity recognition datasets and workflows
Human Activity Recognition (HAR), based on machine and deep learning algorithms is considered one of the most promising technologies to monitor professional and daily life activities for different categories of people (e. g., athletes, elderly, kids, employers) in order to provide a variety of services related, for example to well-being, empowering of technical performances, prevention of risky situation, and educational purposes.
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