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ICCV
2005
IEEE
16 years 9 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu
CVPR
2009
IEEE
17 years 2 months ago
Active Volume Models for 3D Medical Image Segmentation
In this paper, we propose a novel predictive model for object boundary, which can integrate information from any sources. The model is a dynamic “object” model whose manifes...
Tian Shen (Lehigh University), Hongsheng Li (Lehig...
UAI
1996
15 years 8 months ago
Bayesian Learning of Loglinear Models for Neural Connectivity
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Kathryn B. Laskey, Laura Martignon
AMFG
2005
IEEE
203views Biometrics» more  AMFG 2005»
16 years 1 months ago
Facial Expression Analysis Using Nonlinear Decomposable Generative Models
We present a new framework to represent and analyze dynamic facial motions using a decomposable generative model. In this paper, we consider facial expressions which lie on a one d...
Chan-Su Lee, Ahmed M. Elgammal
CVPR
2005
IEEE
16 years 9 months ago
Simultaneous Modeling and Tracking (SMAT) of Feature Sets
A novel method for the simultaneous modeling and tracking (SMAT) of a feature set during motion sequence is proposed. The method requires no prior information. Instead the a poste...
N. D. H. Dowson, Richard Bowden