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GCB
2000
Springer
137views Biometrics» more  GCB 2000»
13 years 8 months ago
Detecting Sporadic Recombination in DNA Alignments with Hidden Markov Models
Conventional phylogenetic tree estimation methods assume that all sites in a DNA multiple alignment have the same evolutionary history. This assumption is violated in data sets fro...
Dirk Husmeier, Frank Wright
EMNLP
2004
13 years 6 months ago
Comparing and Combining Generative and Posterior Probability Models: Some Advances in Sentence Boundary Detection in Speech
We compare and contrast two different models for detecting sentence-like units in continuous speech. The first approach uses hidden Markov sequence models based on N-grams and max...
Yang Liu, Andreas Stolcke, Elizabeth Shriberg, Mar...
ICPR
2008
IEEE
13 years 11 months ago
A probabilistic model for classifying segmented images
In this work we introduce a probabilistic model for classifying segmented images. The proposed classifier is very general and it can deal both with images that were segmented wit...
Liang Wu, Predrag Neskovic, Leon N. Cooper
MVA
2007
179views Computer Vision» more  MVA 2007»
13 years 4 months ago
Multi-object trajectory tracking
The majority of existing tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework using a Hidden Markov Model, where the distribution ...
Mei Han, Wei Xu, Hai Tao, Yihong Gong
CVPR
2004
IEEE
14 years 6 months ago
An Algorithm for Multiple Object Trajectory Tracking
Most tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework called Hidden Markov Model, where the distribution of the object state a...
Mei Han, Wei Xu, Hai Tao, Yihong Gong