Study of Semi-supervised Deep Learning Methods on Human Activity Recognition Tasks
This project focuses on semi-supervised human activity recognition (HAR) tasks, in which the inputs are partly labeled time series data acquired from sensors such as accelerometer data, and the outputs are predefined human activities. Most state-of-the-art existing work in HAR area is supervised now...
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| Format: | Others |
| Language: | English |
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KTH, Robotik, perception och lärande, RPL
2019
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-241366 |