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» A Statistical Shape Model without Using Landmarks
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ICPR
2006
IEEE
14 years 10 months ago
Shape-based Discrimination and Classification of Cortical Surfaces
Advances in medical imaging technique make it possible to study shape variations of neuroanatomical structures in vivo, which has been proved useful in the study of neuropathology...
Arthur K. Liu, Bruce Fischl, Florent Ségonn...
ICCV
2005
IEEE
14 years 2 months ago
Mutual Information-Based 3D Surface Matching with Applications to Face Recognition and Brain Mapping
Face recognition and many medical imaging applications require the computation of dense correspondence vector fields that match one surface with another. In brain imaging, surfac...
Yalin Wang, Ming-Chang Chiang, Paul M. Thompson
GMP
2006
IEEE
126views Solid Modeling» more  GMP 2006»
14 years 3 months ago
Interactive Face-Replacements for Modeling Detailed Shapes
In this paper, we present a method that allows novice users to interactively create partially self-similar manifold surfaces without relying on shape grammars or fractal methods. ...
Eric Landreneau, Ergun Akleman, John Keyser
ACII
2005
Springer
13 years 11 months ago
The Bunch-Active Shape Model
Active Shape Model (ASM) is one of the most powerful statistical tools for face image alignment. In this paper, we propose a novel method, called Bunch-Active Shape Model (Bunch-AS...
Jingcai Fan, Hongxun Yao, Wen Gao, Yazhou Liu, Xin...
EMNLP
2010
13 years 7 months ago
Minimum Error Rate Training by Sampling the Translation Lattice
Minimum Error Rate Training is the algorithm for log-linear model parameter training most used in state-of-the-art Statistical Machine Translation systems. In its original formula...
Samidh Chatterjee, Nicola Cancedda