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ICIP
2007
IEEE
14 years 8 months ago
Large Scale Learning of Active Shape Models
We propose a framework to learn statistical shape models for faces as piecewise linear models. Specifically, our methodology builds upon primitive active shape models(ASM) to hand...
Atul Kanaujia, Dimitris N. Metaxas
MICCAI
2006
Springer
14 years 7 months ago
Boosting and Nonparametric Based Tracking of Tagged MRI Cardiac Boundaries
Abstract. In this paper we present an accurate cardiac boundary tracking method for 2D tagged MRI time sequences. This method naturally integrates the motion and the static local a...
Zhen Qian, Dimitris N. Metaxas, Leon Axel
JMLR
2006
120views more  JMLR 2006»
13 years 6 months ago
Learning Parts-Based Representations of Data
Many perceptual models and theories hinge on treating objects as a collection of constituent parts. When applying these approaches to data, a fundamental problem arises: how can w...
David A. Ross, Richard S. Zemel
CORR
2011
Springer
222views Education» more  CORR 2011»
12 years 10 months ago
Weakly Supervised Learning of Foreground-Background Segmentation using Masked RBMs
Abstract. We propose an extension of the Restricted Boltzmann Machine (RBM) that allows the joint shape and appearance of foreground objects in cluttered images to be modeled indep...
Nicolas Heess, Nicolas Le Roux, John M. Winn
ISBI
2009
IEEE
14 years 1 months ago
Instance-Based Generative Biological Shape Modeling
Biological shape modeling is an essential task that is required for systems biology efforts to simulate complex cell behaviors. Statistical learning methods have been used to buil...
Tao Peng, Wei Wang, Gustavo K. Rohde, Robert F. Mu...