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ESANN
2008
9 years 2 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
DAGSTUHL
2007
9 years 2 months ago
Logical Particle Filtering
Abstract. In this paper, we consider the problem of filtering in relational hidden Markov models. We present a compact representation for such models and an associated logical par...
Luke S. Zettlemoyer, Hanna M. Pasula, Leslie Pack ...
ADMI
2010
Springer
9 years 2 months ago
Probabilistic Modeling of Mobile Agents' Trajectories
Abstract. We present a method for learning characteristic motion patterns of mobile agents. The method works on two levels. On the first level, it uses the expectation-maximization...
Stepán Urban, Michal Jakob, Michal Pechouce...
ICB
2007
Springer
183views Biometrics» more  ICB 2007»
9 years 3 months ago
Factorial Hidden Markov Models for Gait Recognition
Gait recognition is an effective approach for human identification at a distance. During the last decade, the theory of hidden Markov models (HMMs) has been used successfully in th...
Changhong Chen, Jimin Liang, Haihong Hu, Licheng J...
COLT
2008
Springer
9 years 3 months ago
Combining Expert Advice Efficiently
We show how models for prediction with expert advice can be defined concisely and clearly using hidden Markov models (HMMs); standard HMM algorithms can then be used to efficientl...
Wouter M. Koolen, Steven de Rooij
CIVR
2008
Springer
207views Image Analysis» more  CIVR 2008»
9 years 3 months ago
Accumulated motion energy fields estimation and representation for semantic event detection
In this paper, a motion-based approach for detecting highlevel semantic events in video sequences is presented. Its main characteristic is its generic nature, i.e. it can be direc...
Georgios Th. Papadopoulos, Vasileios Mezaris, Ioan...
AUSAI
2008
Springer
9 years 3 months ago
Propositionalisation of Profile Hidden Markov Models for Biological Sequence Analysis
Hidden Markov Models are a widely used generative model for analysing sequence data. A variant, Profile Hidden Markov Models are a special case used in Bioinformatics to represent,...
Stefan Mutter, Bernhard Pfahringer, Geoffrey Holme...
FLAIRS
2008
9 years 3 months ago
Learning Dynamic Naive Bayesian Classifiers
Hidden Markov models are a powerful technique to model and classify temporal sequences, such as in speech and gesture recognition. However, defining these models is still an art: ...
Miriam Martínez, Luis Enrique Sucar
AUSAI
2003
Springer
9 years 5 months ago
Token Identification Using HMM and PPM Models
Hidden markov models (HMMs) and prediction by partial matching models (PPM) have been successfully used in language processing tasks including learning-based token identification. ...
Yingying Wen, Ian H. Witten, Dianhui Wang
FGR
2004
IEEE
135views Biometrics» more  FGR 2004»
9 years 5 months ago
Bayesian Fusion of Hidden Markov Models for Understanding Bimanual Movements
Understanding hand and body gestures is a part of a wide spectrum of current research in computer vision and Human-Computer Interaction. A part of this can be the recognition of m...
Atid Shamaie, Alistair Sutherland
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