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» A stochastic memoizer for sequence data
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ICML
2001
IEEE
14 years 6 months ago
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
John D. Lafferty, Andrew McCallum, Fernando C. N. ...
CVPR
2005
IEEE
14 years 7 months ago
Full Body Tracking from Multiple Views Using Stochastic Sampling
We present a novel approach for full body pose tracking using stochastic sampling. A volumetric reconstruction of a person is extracted from silhouettes in multiple video images. ...
Roland Kehl, Matthieu Bray, Luc J. Van Gool
BMCBI
2008
93views more  BMCBI 2008»
13 years 5 months ago
Hybrid MM/SVM structural sensors for stochastic sequential data
In this paper we present preliminary results stemming from a novel application of Markov Models and Support Vector Machines to splice site classification of Intron-Exon and Exon-I...
Brian Roux, Stephen Winters-Hilt
CVPR
2007
IEEE
14 years 7 months ago
Learning Dynamic Event Descriptions in Image Sequences
Automatic detection of dynamic events in video sequences has a variety of applications including visual surveillance and monitoring, video highlight extraction, intelligent transp...
Harini Veeraraghavan, Nikolaos Papanikolopoulos, P...
BMCBI
2011
12 years 12 months ago
Multithreaded comparative RNA secondary structure prediction using stochastic context-free grammars
Background: The prediction of the structure of large RNAs remains a particular challenge in bioinformatics, due to the computational complexity and low levels of accuracy of state...
Zsuzsanna Sukosd, Bjarne Knudsen, Morten Vaerum, J...