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CIARP
2009
Springer
14 years 2 months ago
Learning Relational Grammars from Sequences of Actions
Many tasks can be described by sequences of actions that normally exhibit some form of structure and that can be represented by a grammar. This paper introduces FOSeq, an algorithm...
Blanca Vargas-Govea, Eduardo F. Morales
ICMCS
2005
IEEE
173views Multimedia» more  ICMCS 2005»
14 years 1 months ago
A Multi-Modal Mixed-State Dynamic Bayesian Network for Robust Meeting Event Recognition from Disturbed Data
In this work we present a novel multi-modal mixed-state dynamic Bayesian network (DBN) for robust meeting event classification. The model uses information from lapel microphones,...
Marc Al-Hames, Gerhard Rigoll
IJCAI
2007
13 years 9 months ago
Dynamically Weighted Hidden Markov Model for Spam Deobfuscation
Spam deobfuscation is a processing to detect obfuscated words appeared in spam emails and to convert them back to the original words for correct recognition. Lexicon tree hidden M...
Seunghak Lee, Iryoung Jeong, Seungjin Choi
ICANN
2009
Springer
14 years 10 days ago
Switching Hidden Markov Models for Learning of Motion Patterns in Videos
Abstract. Building on the current understanding of neural architecture of the visual cortex, we present a graphical model for learning and classification of motion patterns in vid...
Matthias Höffken, Daniel Oberhoff, Marina Kol...
ML
1998
ACM
139views Machine Learning» more  ML 1998»
13 years 7 months ago
The Hierarchical Hidden Markov Model: Analysis and Applications
We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our m...
Shai Fine, Yoram Singer, Naftali Tishby