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ICML
1999
IEEE
16 years 7 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox
ICIP
2004
IEEE
16 years 7 months ago
Stochastic modeling of volume images with a 3-d hidden markov model
Over the years, researchers in the image analysis community have successfully used various statistical modeling methods to segment, classify, and annotate digital images. In this ...
Jia Li, Dhiraj Joshi, James Ze Wang
ICIP
2002
IEEE
16 years 7 months ago
Modeling object classes in aerial images using hidden Markov models
A canonical model is proposed for object classes in aerial images. This model is motivated by the observation that geographic regions of interest are characterized by collections ...
Shawn Newsam, Sitaram Bhagavathy, B. S. Manjunath
KDD
2008
ACM
115views Data Mining» more  KDD 2008»
16 years 6 months ago
SPIRAL: efficient and exact model identification for hidden Markov models
Hidden Markov models (HMMs) have received considerable attention in various communities (e.g, speech recognition, neurology and bioinformatic) since many applications that use HMM...
Yasuhiro Fujiwara, Yasushi Sakurai, Masashi Yamamu...
ICPR
2008
IEEE
16 years 17 days ago
Embedding HMM's-based models in a Euclidean space: The topological hidden Markov models
One of the major limitations of HMM-based models is the inability to cope with topology: When applied to a visible observation (VO) sequence, HMM-based techniques have difficulty ...
Djamel Bouchaffra