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» Learning from Highly Structured Data by Decomposition
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PAMI
2008
119views more  PAMI 2008»
14 years 9 months ago
Triplet Markov Fields for the Classification of Complex Structure Data
We address the issue of classifying complex data. We focus on three main sources of complexity, namely, the high dimensionality of the observed data, the dependencies between these...
Juliette Blanchet, Florence Forbes
CVPR
2011
IEEE
14 years 6 months ago
Learning Effective Human Pose Estimation from Inaccurate Annotation
The task of 2-D articulated human pose estimation in natural images is extremely challenging due to the high level of variation in human appearance. These variations arise from di...
Sam Johnson, Mark Everingham
CGF
2010
98views more  CGF 2010»
14 years 10 months ago
Image Synthesis for Branching Structures
We present a set of techniques for the synthesis of artificial images that depict branching structures like rivers, cracks, lightning, mountain ranges, or blood vessels. The centr...
Dominik Sibbing, Darko Pavic, Leif Kobbelt
ICCS
2001
Springer
15 years 2 months ago
Learning to Generate CGs from Domain Specific Sentences
Automatically generating Conceptual Graphs (CGs) [1] from natural language sentences is a difficult task in using CG as a semantic (knowledge) representation language for natural l...
Lei Zhang, Yong Yu
UAI
1997
14 years 11 months ago
Exploring Parallelism in Learning Belief Networks
It has been shown that a class of probabilistic domain models cannot be learned correctly by several existing algorithms which employ a single-link lookahead search. When a multil...
Tongsheng Chu, Yang Xiang