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NN
1997
Springer
174views Neural Networks» more  NN 1997»
13 years 11 months ago
Learning Dynamic Bayesian Networks
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Zoubin Ghahramani
ICALT
2008
IEEE
14 years 1 months ago
Designing a Dynamic Bayesian Network for Modeling Students' Learning Styles
When using Learning Object Repositories, it is interesting to have mechanisms to select the more adequate objects for each student. For this kind of adaptation, it is important to...
Cristina Carmona, Gladys Castillo, Eva Millá...
AVSS
2008
IEEE
14 years 1 months ago
Person Tracking with Audio-Visual Cues Using the Iterative Decoding Framework
Tracking humans in an indoor environment is an essential part of surveillance systems. Vision based and microphone array based trackers have been extensively researched in the pas...
Shankar T. Shivappa, Mohan M. Trivedi, Bhaskar D. ...
ICCV
2003
IEEE
14 years 23 days ago
Tracking Articulated Hand Motion with Eigen Dynamics Analysis
This paper introduces the concept of eigen-dynamics and proposes an eigen dynamics analysis (EDA) method to learn the dynamics of natural hand motion from labelled sets of motion ...
Hanning Zhou, Thomas S. Huang
LREC
2010
190views Education» more  LREC 2010»
13 years 9 months ago
Applying a Dynamic Bayesian Network Framework to Transliteration Identification
Identification of transliterations is aimed at enriching multilingual lexicons and improving performance in various Natural Language Processing (NLP) applications including Cross ...
Peter Nabende