Learning patterns of human behavior from sensor data is extremely important for high-level activity inference. We show how to extract and label a personās activities and signiļ¬...
Abstract. This paper introduces Higher-Order Bayesian Networks, a probabilistic reasoning formalism which combines the efļ¬cient reasoning mechanisms of Bayesian Networks with the...
Research in advanced context-aware systems has clearly shown a need to capture the inherent uncertainty in the physical world, especially in human behavior. Modelling approaches th...
Michael Angermann, Patrick Robertson, Thomas Stran...
This paper explores basic aspects of the immune system and proposes a novel immune network model with the main goals of clustering and filtering unlabeled numerical data sets. It ...
Learning patterns of human behavior from sensor data is extremely important for high-level activity inference. We show how to extract a personās activities and signiļ¬cant plac...