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» Representing Systems with Hidden State
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115
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ECSQARU
2007
Springer
15 years 8 months ago
Forward-Backward-Viterbi Procedures in the Transferable Belief Model for State Sequence Analysis Using Belief Functions
Abstract. The Transferable Belief Model (TBM) relies on belief functions and enables one to represent and combine a variety of knowledge from certain up to ignorance as well as con...
Emmanuel Ramasso, Michèle Rombaut, Denis Pe...
ICASSP
2011
IEEE
14 years 5 months ago
A unified approach to real time audio-to-score and audio-to-audio alignment using sequential Montecarlo inference techniques
We present a methodology for the real time alignment of music signals using sequential Montecarlo inference techniques. The alignment problem is formulated as the state tracking o...
Nicola Montecchio, Arshia Cont
101
Voted
ICIP
2005
IEEE
16 years 3 months ago
Flame detection in video using hidden Markov models
This paper proposes a novel method to detect flames in video by processing the data generated by an ordinary camera monitoring a scene. In addition to ordinary motion and color cl...
A. Enis Çetin, B. Ugur Töreyin, Yigith...
124
Voted
JAIR
2002
120views more  JAIR 2002»
15 years 1 months ago
Learning Geometrically-Constrained Hidden Markov Models for Robot Navigation: Bridging the Topological-Geometrical Gap
Hidden Markov models hmms and partially observable Markov decision processes pomdps provide useful tools for modeling dynamical systems. They are particularly useful for represent...
Hagit Shatkay, Leslie Pack Kaelbling
SOUPS
2009
ACM
15 years 8 months ago
Revealing hidden context: improving mental models of personal firewall users
The Windows Vista personal firewall provides its diverse users with a basic interface that hides many operational details. However, concealing the impact of network context on th...
Fahimeh Raja, Kirstie Hawkey, Konstantin Beznosov