JMLR
2012
12 years 9 days ago
2012
To relax the homogeneity assumption of classical dynamic Bayesian networks (DBNs), various recent studies have combined DBNs with multiple changepoint processes. The underlying as...
PR
2011
13 years 21 days ago
2011
This paper aims to address the problem of anomaly detection and discrimination in complex behaviours, where anomalies are subtle and difficult to detect owing to the complex tempo...
ICASSP
2011
IEEE
13 years 1 months ago
2011
IEEE
We address the problem of pronunciation variation in conversational speech with a context-dependent articulatory featurebased model. The model is an extension of previous work usi...
JMLR
2010
13 years 4 months ago
2010
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
EXPERT
2010
13 years 7 months ago
2010
Human behavior recognition is one of the most important and challenging objectives performed by intelligent vision systems. Several issues must be faced in this domain ranging fro...
KI
2010
Springer
13 years 7 months ago
2010
Springer
Recognizing human intentions is part of the decision process in many technical devices. In order to achieve natural interaction, the required estimation quality and the used comput...
ACL
2010
13 years 8 months ago
2010
Most previous work on trainable language generation has focused on two paradigms: (a) using a statistical model to rank a set of generated utterances, or (b) using statistics to i...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Classical dynamic Bayesian networks (DBNs) are based on the homogeneous Markov assumption and cannot deal with heterogeneity and non-stationarity in temporal processes. Various ap...
IJAR
2002
13 years 9 months ago
2002
The usual methods of applying Bayesian networks to the modeling of temporal processes, such as Dean and Kanazawa's dynamic Bayesian networks (DBNs), consist in discretizing t...
JMM2
2007
13 years 9 months ago
2007
Abstract— Activity recognition in video streams is increasingly important for both the computer vision and artificial intelligence communities. Activity recognition has many app...