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» Using hidden Markov models and wavelets for face recognition
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JMLR
2006
143views more  JMLR 2006»
13 years 7 months ago
Segmental Hidden Markov Models with Random Effects for Waveform Modeling
This paper proposes a general probabilistic framework for shape-based modeling and classification of waveform data. A segmental hidden Markov model (HMM) is used to characterize w...
Seyoung Kim, Padhraic Smyth
ICPR
2004
IEEE
14 years 8 months ago
A Hybrid Face Recognition Method using Markov Random Fields
We propose a hybrid face recognition method that combines holistic and feature analysis-based approaches using a Markov random field (MRF) model. The face images are divided into ...
Dimitris N. Metaxas, Rui Huang, Vladimir Pavlovic
ICASSP
2011
IEEE
12 years 11 months ago
Using multiple visual tandem streams in audio-visual speech recognition
The method which is called the “tandem approach” in speech recognition has been shown to increase performance by using classifier posterior probabilities as observations in a...
Ibrahim Saygin Topkaya, Hakan Erdogan
TSP
2008
180views more  TSP 2008»
13 years 7 months ago
Support Vector Machine Training for Improved Hidden Markov Modeling
We present a discriminative training algorithm, that uses support vector machines (SVMs), to improve the classification of discrete and continuous output probability hidden Markov ...
Alba Sloin, David Burshtein
ICPR
2000
IEEE
13 years 12 months ago
Hidden Markov Random Field Based Approach for Off-Line Handwritten Chinese Character Recognition
This paper presents a Hidden Markov Mesh Random Field (HMMRF) based approach for off-line handwritten Chinese characters recognition using statistical observation sequences embedd...
Qing Wang, Rongchun Zhao, Zheru Chi, David Dagan F...