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» Image Distance Using Hidden Markov Models
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CVPR
2007
IEEE
14 years 9 months ago
Discriminative Learning of Dynamical Systems for Motion Tracking
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
Minyoung Kim, Vladimir Pavlovic
ICMCS
2005
IEEE
173views Multimedia» more  ICMCS 2005»
14 years 1 months ago
A Multi-Modal Mixed-State Dynamic Bayesian Network for Robust Meeting Event Recognition from Disturbed Data
In this work we present a novel multi-modal mixed-state dynamic Bayesian network (DBN) for robust meeting event classification. The model uses information from lapel microphones,...
Marc Al-Hames, Gerhard Rigoll
MICCAI
2003
Springer
14 years 8 months ago
A New Brain Segmentation Framework
We present a new brain segmentation framework which we apply to T1-weighted magnetic resonance image segmentation. The innovation of the algorithm in comparison to the state-of-the...
Torsten Butz, Patric Hagmann, Eric Tardif, Reto Me...
ICASSP
2010
IEEE
13 years 8 months ago
Phone recognition using Restricted Boltzmann Machines
For decades, Hidden Markov Models (HMMs) have been the state-of-the-art technique for acoustic modeling despite their unrealistic independence assumptions and the very limited rep...
Abdel-rahman Mohamed, Geoffrey E. Hinton
ICIP
2001
IEEE
14 years 9 months ago
VISMap: an interactive image/video retrieval system using visualization and concept maps
Images and videos can be indexed by multiple features at different levels, such as color, texture, motion, and text annotation. Organizing this information into a system so that u...
William Chen, Shih-Fu Chang