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ICIP
1998
IEEE
14 years 7 months ago
Deriving Facial Articulation Models from Image Sequences
In this paper, human facial articulation models are derived from frontal and side view image sequences using connected vibrations non-rigid motion tracking algorithm. First, a 3D ...
Hai Tao, Thomas S. Huang
BMCBI
2010
141views more  BMCBI 2010»
13 years 5 months ago
Computing and visually analyzing mutual information in molecular co-evolution
Background: Selective pressure in molecular evolution leads to uneven distributions of amino acids and nucleotides. In fact one observes correlations among such constituents due t...
Sebastian Bremm, Tobias Schreck, Patrick Boba, Ste...
NIPS
2004
13 years 6 months ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra
CONNECTION
2004
98views more  CONNECTION 2004»
13 years 5 months ago
Self-refreshing memory in artificial neural networks: learning temporal sequences without catastrophic forgetting
While humans forget gradually, highly distributed connectionist networks forget catastrophically: newly learned information often completely erases previously learned information. ...
Bernard Ans, Stephane Rousset, Robert M. French, S...
MICCAI
2009
Springer
14 years 6 months ago
Biomechanically-Constrained 4D Estimation of Myocardial Motion
We propose a method for the analysis of Magnetic Resonance (MR) cardiac images with the goal of reconstructing the motion of the ventricular walls. The main feature of our method i...
Hari Sundar, Christos Davatzikos, George Biros