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BMCBI
2011
14 years 7 months ago
Learning sparse models for a dynamic Bayesian network classifier of protein secondary structure
Background: Protein secondary structure prediction provides insight into protein function and is a valuable preliminary step for predicting the 3D structure of a protein. Dynamic ...
Zafer Aydin, Ajit Singh, Jeff Bilmes, William Staf...
155
Voted
3DOR
2010
14 years 10 months ago
Learning the Compositional Structure of Man-Made Objects for 3D Shape Retrieval
While approaches based on local features play a more and more important role for 3D shape retrieval, the problems of feature selection and similarity measurement between sets of l...
Raoul Wessel, Reinhard Klein
161
Voted
LATIN
2010
Springer
15 years 10 months ago
Time Complexity of Distributed Topological Self-stabilization: The Case of Graph Linearization
Topological self-stabilization is an important concept to build robust open distributed systems (such as peer-to-peer systems) where nodes can organize themselves into meaningful n...
Dominik Gall, Riko Jacob, Andréa W. Richa, ...
130
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IPPS
2006
IEEE
15 years 9 months ago
A multiprocessor architecture for the massively parallel model GCA
The GCA (Global Cellular Automata) model consists of a collection of cells which change their states synchronously depending on the states of their neighbors like in the classical...
Wolfgang Heenes, Rolf Hoffmann, Johannes Jendrsczo...
133
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CAIP
2003
Springer
222views Image Analysis» more  CAIP 2003»
15 years 9 months ago
Learning Statistical Structure for Object Detection
Abstract. Many classes of images exhibit sparse structuring of statistical dependency. Each variable has strong statistical dependency with a small number of other variables and ne...
Henry Schneiderman