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» Learning and prediction of slip from visual information
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CVPR
2010
IEEE
14 years 4 months ago
Learning a Hierarchy of Discriminative Space-Time Neighborhood Features for Human Action Recognition
Recent work shows how to use local spatio-temporal features to learn models of realistic human actions from video. However, existing methods typically rely on a predefined spatial...
Adriana Kovashka, Kristen Grauman
RECOMB
2011
Springer
12 years 10 months ago
Rich Parameterization Improves RNA Structure Prediction
Motivation. Current approaches to RNA structure prediction range from physics-based methods, which rely on thousands of experimentally-measured thermodynamic parameters, to machin...
Shay Zakov, Yoav Goldberg, Michael Elhadad, Michal...
BMCBI
2006
150views more  BMCBI 2006»
13 years 7 months ago
Predicting protein subcellular locations using hierarchical ensemble of Bayesian classifiers based on Markov chains
Background: The subcellular location of a protein is closely related to its function. It would be worthwhile to develop a method to predict the subcellular location for a given pr...
Alla Bulashevska, Roland Eils
ECOI
2007
80views more  ECOI 2007»
13 years 7 months ago
EcoLens: Integration and interactive visualization of ecological datasets
Complex multi-dimensional datasets are now pervasive in science and elsewhere in society. Better interactive tools are needed for visual data exploration so that patterns in such ...
Cynthia Sims Parr, Bongshin Lee, Benjamin B. Beder...
ICPR
2008
IEEE
14 years 9 months ago
Detecting and ordering salient regions for efficient browsing
We describe an ensemble approach to learning1 salient regions from data partitioned according to the2 distributed processing requirements of large-scale sim-3 ulations. The volume...
Larry Shoemaker, Robert E. Banfield, Larry O. Hall...