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» Optimizing Feature Sets for Structured Data
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EMMCVPR
2001
Springer
15 years 2 months ago
Designing the Minimal Structure of Hidden Markov Model by Bisimulation
Hidden Markov Models (HMMs) are an useful and widely utilized approach to the modeling of data sequences. One of the problems related to this technique is finding the optimal stru...
Manuele Bicego, Agostino Dovier, Vittorio Murino
PAMI
1998
197views more  PAMI 1998»
14 years 9 months ago
Inference of Integrated Surface, Curve, and Junction Descriptions From Sparse 3D Data
—We are interested in descriptions of 3D data sets, as obtained from stereo or a 3D digitizer. We therefore consider as input a sparse set of points, possibly associated with cer...
Chi-Keung Tang, Gérard G. Medioni
WABI
2005
Springer
120views Bioinformatics» more  WABI 2005»
15 years 3 months ago
Multiple Structural RNA Alignment with Lagrangian Relaxation
In contrast to proteins, many classes of functionally related RNA molecules show a rather weak sequence conservation but instead a fairly well conserved secondary structure. Hence ...
Markus Bauer, Gunnar W. Klau, Knut Reinert
IEICET
2008
67views more  IEICET 2008»
14 years 10 months ago
Learning of Finite Unions of Tree Patterns with Internal Structured Variables from Queries
We consider the polynomial time learnability of finite unions of ordered tree patterns with internal structured variables, in the query learning model of Angluin (1988). An ordered...
Satoshi Matsumoto, Takayoshi Shoudai, Tomoyuki Uch...
ICDAR
2009
IEEE
14 years 7 months ago
Stochastic Segment Modeling for Offline Handwriting Recognition
In this paper, we present a novel approach for incorporating structural information into the hidden Markov Modeling (HMM) framework for offline handwriting recognition. Traditiona...
Premkumar Natarajan, Krishna Subramanian, Anurag B...