In this paper, three different measures of uncertainty have been used for selecting the most informative data points and their performance have been evaluated by using real world data sets.
Automated activity recognition systems that use probabilistic models require labeled data sets in training phase for learning the model parameters. The parameters are different for every person and every environment. Therefore, for every person or …
The performance of activity recognition systems depends on annotated training data. Obtaining annotated data is a costly and burdensome task. The need for annotated data for activity recognition systems using Hidden Markov models can be reduced by …