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PAMI
2010
238views more  PAMI 2010»
15 years 2 months ago
Tracking Motion, Deformation, and Texture Using Conditionally Gaussian Processes
—We present a generative model and inference algorithm for 3D nonrigid object tracking. The model, which we call G-flow, enables the joint inference of 3D position, orientation, ...
Tim K. Marks, John R. Hershey, Javier R. Movellan
ECAL
2001
Springer
15 years 8 months ago
The Survival of the Smallest: Stability Conditions for the Cultural Evolution of Compositional Language
Abstract. Recent work in the field of computational evolutionary linguistics suggests that the dynamics arising from the cultural evolution of language can explain the emergence o...
Henry Brighton, Simon Kirby
KDD
2009
ACM
178views Data Mining» more  KDD 2009»
16 years 4 months ago
Constrained optimization for validation-guided conditional random field learning
Conditional random fields(CRFs) are a class of undirected graphical models which have been widely used for classifying and labeling sequence data. The training of CRFs is typicall...
Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E...
TVCG
2008
147views more  TVCG 2008»
15 years 4 months ago
Cerebral: Visualizing Multiple Experimental Conditions on a Graph with Biological Context
Systems biologists use interaction graphs to model the behavior of biological systems at the molecular level. In an iterative process, such biologists observe the reactions of livi...
Aaron Barsky, Tamara Munzner, Jennifer L. Gardy, R...
CVBIA
2005
Springer
15 years 9 months ago
Segmenting Brain Tumors with Conditional Random Fields and Support Vector Machines
Abstract. Markov Random Fields (MRFs) are a popular and wellmotivated model for many medical image processing tasks such as segmentation. Discriminative Random Fields (DRFs), a dis...
Chi-Hoon Lee, Mark Schmidt, Albert Murtha, Aalo Bi...