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NIPS
2008
13 years 10 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink
MM
2010
ACM
169views Multimedia» more  MM 2010»
13 years 9 months ago
CO3 for ultra-fast and accurate interactive segmentation
This paper presents an interactive image segmentation framework which is ultra-fast and accurate. Our framework, termed "CO3", consists of three components: COupled repr...
Yibiao Zhao, Song Chun Zhu, Siwei Luo
IJON
2006
189views more  IJON 2006»
13 years 8 months ago
Storing and restoring visual input with collaborative rank coding and associative memory
Associative memory in cortical circuits has been held as a major mechanism for content-addressable memory. Hebbian synapses implement associative memory efficiently when storing s...
Martin Rehn, Friedrich T. Sommer
CVPR
2000
IEEE
14 years 10 months ago
A Curve Evolution Approach to Smoothing and Segmentation Using the Mumford-Shah Functional
In this work, we approach the classic Mumford-Shah problem from a curve evolution perspective. In particular, we let a given family of curves define the boundaries between regions...
Andy Tsai, Anthony J. Yezzi, Alan S. Willsky
VISUALIZATION
2005
IEEE
14 years 2 months ago
Particle and Texture Based Spatiotemporal Visualization of Time-Dependent Vector Fields
We propose a hybrid particle and texture based approach for the visualization of time-dependent vector fields. The underlying spacetime framework builds a dense vector field rep...
Daniel Weiskopf, Frederik Schramm, Gordon Erlebach...