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» Complexity of Inference in Graphical Models
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CVPR
2008
IEEE
14 years 11 months ago
Max Margin AND/OR Graph learning for parsing the human body
We present a novel structure learning method, Max Margin AND/OR Graph (MM-AOG), for parsing the human body into parts and recovering their poses. Our method represents the human b...
Long Zhu, Yuanhao Chen, Yifei Lu, Chenxi Lin, Alan...
ICVS
2001
Springer
14 years 1 months ago
A Framework for Generic State Estimation in Computer Vision Applications
Abstract. Experimenting and building integrated, operational systems in computational vision poses both theoretical and practical challenges, involving methodologies from control t...
Cristian Sminchisescu, Alexandru Telea
NIPS
2008
13 years 10 months ago
Partially Observed Maximum Entropy Discrimination Markov Networks
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
Jun Zhu, Eric P. Xing, Bo Zhang
SIMUTOOLS
2008
13 years 10 months ago
Simulating wireless and mobile networks in OMNeT++ the MiXiM vision
Wireless communication has attracted considerable interest in the research community, and many wireless networks are evaluated using discrete event simulators like OMNeT++. Althou...
A. Köpke, M. Swigulski, K. Wessel, D. Willkom...
VIS
2006
IEEE
128views Visualization» more  VIS 2006»
14 years 10 months ago
Hierarchy-based 3-D Visualization of Homologous Gene Expression across Different Organisms
With the explosive growth of proteomic and expression data of homologous genes, it becomes necessary to explore new methods to visualize and analyze related gene expression data t...
Li Jin, Karl V. Steiner, Carl J. Schmidt, Keith...