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» A Preference Model for Structured Supervised Learning Tasks
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ICCV
2007
IEEE
15 years 6 months ago
Fast Automatic Heart Chamber Segmentation from 3D CT Data Using Marginal Space Learning and Steerable Features
Multi-chamber heart segmentation is a prerequisite for global quantification of the cardiac function. The complexity of cardiac anatomy, poor contrast, noise or motion artifacts ...
Yefeng Zheng, Adrian Barbu, Bogdan Georgescu, Mich...
ICANN
2001
Springer
15 years 4 months ago
Independent Variable Group Analysis
Humans tend to group together related properties in order to understand complex phenomena. When modeling large problems with limited representational resources, it is important to...
Krista Lagus, Esa Alhoniemi, Harri Valpola
ACL
2009
14 years 9 months ago
Unsupervised Multilingual Grammar Induction
We investigate the task of unsupervised constituency parsing from bilingual parallel corpora. Our goal is to use bilingual cues to learn improved parsing models for each language ...
Benjamin Snyder, Tahira Naseem, Regina Barzilay
ICCV
2011
IEEE
13 years 11 months ago
Decision Tree Fields
This paper introduces a new formulation for discrete image labeling tasks, the Decision Tree Field (DTF), that combines and generalizes random forests and conditional random fiel...
Sebastian Nowozin, Carsten Rother, Shai Bagon, Ban...
CVPR
2008
IEEE
16 years 1 months ago
Unsupervised discovery of visual object class hierarchies
Objects in the world can be arranged into a hierarchy based on their semantic meaning (e.g. organism ? animal ? feline ? cat). What about defining a hierarchy based on the visual ...
Josef Sivic, Bryan C. Russell, Andrew Zisserman, W...