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ECCV
2002
Springer
14 years 9 months ago
Factorial Markov Random Fields
In this paper we propose an extension to the standard Markov Random Field (MRF) model in order to handle layers. Our extension, which we call a Factorial MRF (FMRF), is analogous t...
Junhwan Kim, Ramin Zabih
NIPS
2008
13 years 9 months ago
Extracting State Transition Dynamics from Multiple Spike Trains with Correlated Poisson HMM
Neural activity is non-stationary and varies across time. Hidden Markov Models (HMMs) have been used to track the state transition among quasi-stationary discrete neural states. W...
Kentaro Katahira, Jun Nishikawa, Kazuo Okanoya, Ma...
ICDAR
2009
IEEE
14 years 2 months ago
Unsupervised HMM Adaptation Using Page Style Clustering
In this paper we present an innovative two-stage adaptation approach for handwriting recognition that is based on clustering of similar pages in the training data. In our approach...
Huaigu Cao, Rohit Prasad, Shirin Saleem, Premkumar...
CVPR
2007
IEEE
14 years 9 months ago
Multiview normal field integration using level set methods
In this paper, we propose a new method to integrate multiview normal fields using level sets. In contrast with conventional normal integration algorithms used in shape from shadin...
Ju Yong Chang, Kyoung Mu Lee, Sang Uk Lee
TASLP
2008
140views more  TASLP 2008»
13 years 7 months ago
Acoustic Chord Transcription and Key Extraction From Audio Using Key-Dependent HMMs Trained on Synthesized Audio
We describe an acoustic chord transcription system that uses symbolic data to train hidden Markov models and gives best-of-class frame-level recognition results. We avoid the extre...
Kyogu Lee, Malcolm Slaney