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» Training Deformable Models for Localization
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ACL
2006
13 years 9 months ago
Minimum Risk Annealing for Training Log-Linear Models
When training the parameters for a natural language system, one would prefer to minimize 1-best loss (error) on an evaluation set. Since the error surface for many natural languag...
David A. Smith, Jason Eisner
ICPR
2004
IEEE
14 years 9 months ago
Surface Sculpting with Stochastic Deformable 3D Surfaces
This paper introduces a new stochastic surface model for deformable 3D surfaces and demonstrates its utility for the purpose of 3D sculpting. This is the problem of simple-touse a...
Andrew R. Willis, Jasper Speicher, David B. Cooper
CVPR
2010
IEEE
14 years 1 months ago
Latent Hierarchical Structural Learning for Object Detection
We present a latent hierarchical structural learning method for object detection. An object is represented by a mixture of hierarchical tree models where the nodes represent objec...
Leo Zhu, Yuanhao Chen, Antonio Torralba, Alan Yuil...
WSCG
2003
149views more  WSCG 2003»
13 years 9 months ago
Simulating Deformable Tools with Haptic Feedback in a Virtual Environment
Simulations for training and analysis incorporating haptic feedback are becoming more popular and the sophistication of these simulations is increasing. Many systems now allow a r...
Stephen D. Laycock, A. M. Day
TMI
2008
123views more  TMI 2008»
13 years 8 months ago
ORBIT: A Multiresolution Framework for Deformable Registration of Brain Tumor Images
Abstract--A deformable registration method is proposed for registering a normal brain atlas with images of brain tumor patients. The registration is facilitated by first simulating...
Evangelia I. Zacharaki, Dinggang Shen, Seung-koo L...