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» Hidden Conditional Random Fields for Meeting Segmentation
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ICASSP
2009
IEEE
14 years 8 months ago
Applying discretized articulatory knowledge to dysarthric speech
This paper applies two dynamic Bayes networks that include theoretical and measured kinematic features of the vocal tract, respectively, to the task of labeling phoneme sequences ...
Frank Rudzicz
PAMI
2002
108views more  PAMI 2002»
14 years 10 months ago
Approximate Bayes Factors for Image Segmentation: The Pseudolikelihood Information Criterion (PLIC)
We propose a method for choosing the number of colors or true gray levels in an image; this allows fully automatic segmentation of images. Our underlying probability model is a hid...
Derek C. Stanford, Adrian E. Raftery
ICCV
2009
IEEE
2301views Computer Vision» more  ICCV 2009»
16 years 3 months ago
Class Segmentation and Object Localization with Superpixel Neighborhoods
We propose a method to identify and localize object classes in images. Instead of operating at the pixel level, we advocate the use of superpixels as the basic unit of a class s...
Brian Fulkerson, Andrea Vedaldi, Stefano Soatto
ACL
2006
14 years 11 months ago
Subword-Based Tagging for Confidence-Dependent Chinese Word Segmentation
We proposed a subword-based tagging for Chinese word segmentation to improve the existing character-based tagging. The subword-based tagging was implemented using the maximum entr...
Ruiqiang Zhang, Gen-ichiro Kikui, Eiichiro Sumita
CVPR
2012
IEEE
13 years 24 days ago
Joint 2D-3D temporally consistent semantic segmentation of street scenes
In this paper we propose a novel Conditional Random Field (CRF) formulation for the semantic scene labeling problem which is able to enforce temporal consistency between consecuti...
Georgios Floros, Bastian Leibe