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ESANN
2008
13 years 8 months ago
Word recognition and incremental learning based on neural associative memories and hidden Markov models
Abstract. An architecture for achieving word recognition and incremental learning of new words in a language processing system is presented. The architecture is based on neural ass...
Zöhre Kara Kayikci, Günther Palm
STOC
2005
ACM
84views Algorithms» more  STOC 2005»
14 years 7 months ago
Learning nonsingular phylogenies and hidden Markov models
In this paper, we study the problem of learning phylogenies and hidden Markov models. We call the Markov model nonsingular if all transtion matrices have determinants bounded away...
Elchanan Mossel, Sébastien Roch
ICCV
2003
IEEE
14 years 9 months ago
Recognition of Group Activities using Dynamic Probabilistic Networks
Dynamic Probabilistic Networks (DPNs) are exploited for modelling the temporal relationships among a set of different object temporal events in the scene for a coherent and robust...
Shaogang Gong, Tao Xiang
CSDA
2007
116views more  CSDA 2007»
13 years 7 months ago
Exploring the state sequence space for hidden Markov and semi-Markov chains
The knowledge of the state sequences that explain a given observed sequence for a known hidden Markovian model is the basis of various methods that may be divided into three categ...
Yann Guédon