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» Supervised dimensionality reduction using mixture models
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88
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ICPR
2008
IEEE
16 years 28 days ago
Segmentation by combining parametric optical flow with a color model
We present a simple but efficient model for object segmentation in video scenes that integrates motion and color information in a joint probabilistic framework. Optical flow is mo...
Adrian Ulges, Thomas M. Breuel
78
Voted
ICPR
2006
IEEE
16 years 25 days ago
Competitive Mixtures of Simple Neurons
We propose a competitive finite mixture of neurons (or perceptrons) for solving binary classification problems. Our classifier includes a prior for the weights between different n...
Karthik Sridharan, Matthew J. Beal, Venu Govindara...
ICMCS
2005
IEEE
169views Multimedia» more  ICMCS 2005»
15 years 5 months ago
Dynamic language model adaptation using latent topical information and automatic transcripts
This paper considers dynamic language model adaptation for Mandarin broadcast news recognition. Both contemporary newswire texts and in-domain automatic transcripts were exploited...
Berlin Chen
EMNLP
2009
14 years 9 months ago
Supervised Learning of a Probabilistic Lexicon of Verb Semantic Classes
The work presented in this paper explores a supervised method for learning a probabilistic model of a lexicon of VerbNet classes. We intend for the probabilistic model to provide ...
Yusuke Miyao, Jun-ichi Tsujii
100
Voted
NIPS
2007
15 years 1 months ago
People Tracking with the Laplacian Eigenmaps Latent Variable Model
Reliably recovering 3D human pose from monocular video requires models that bias the estimates towards typical human poses and motions. We construct priors for people tracking usi...
Zhengdong Lu, Miguel Á. Carreira-Perpi&ntil...