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» Image Distance Using Hidden Markov Models
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ICASSP
2011
IEEE
12 years 11 months ago
EM-style optimization of hidden conditional random fields for grapheme-to-phoneme conversion
We have recently proposed an EM-style algorithm to optimize log-linear models with hidden variables. In this paper, we use this algorithm to optimize a hidden conditional random ï...
Georg Heigold, Stefan Hahn, Patrick Lehnen, Herman...
VLDB
2007
ACM
122views Database» more  VLDB 2007»
14 years 8 months ago
MIST: Distributed Indexing and Querying in Sensor Networks using Statistical Models
The modeling of high level semantic events from low level sensor signals is important in order to understand distributed phenomena. For such content-modeling purposes, transformat...
Arnab Bhattacharya, Anand Meka, Ambuj K. Singh
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
14 years 8 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
SSIAI
2000
IEEE
14 years 2 days ago
Unsupervised Dempster-Shafer Fusion of Dependent Sensors
This paper deals with the problem of statistical unsupervised fusion of dependent sensors with its potential applications to multisensor image segmentation. On the one hand, Bayes...
Wojciech Pieczynski
ICIP
2000
IEEE
14 years 3 days ago
Multiscale Texture Segmentation Using Hybrid Contextual Labeling Tree
Wavelet-domain hidden Markov tree (HMT) model has been recently proposed and applied to image processing, e.g., image segmentation. A new multiscale image segmentation method, cal...
Guoliang Fan, Xiang-Gen Xia