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ICML
2004
IEEE
14 years 8 months ago
Learning Bayesian network classifiers by maximizing conditional likelihood
Bayesian networks are a powerful probabilistic representation, and their use for classification has received considerable attention. However, they tend to perform poorly when lear...
Daniel Grossman, Pedro Domingos
ACCV
2009
Springer
14 years 2 months ago
A Dynamic Programming Approach to Maximizing Tracks for Structure from Motion
We present a novel algorithm for improving the accuracy of structure from motion on video sequences. Its goal is to efficiently recover scene structure and camera pose by using dyn...
Jonathan Mooser, Suya You, Ulrich Neumann, Raphael...
ISBI
2006
IEEE
14 years 8 months ago
A statistical framework for DTI segmentation
We address the problem of the segmentation of cerebral white matter structures from diffusion tensor images (DTI). DTI can be estimated from a set of diffusion weighted images and...
Christophe Lenglet, Mikaël Rousson, Rachid De...
ECCV
2002
Springer
14 years 9 months ago
Structure from Planar Motions with Small Baselines
We study the multi-frame structure from motion problem when the camera translates on a plane with small baselines and arbitrary rotations. This case shows up in many practical appl...
John Oliensis, René Vidal
SSIAI
2000
IEEE
14 years 1 days ago
A New Bayesian Relaxation Framework for the Estimation and Segmentation of Multiple Motions
In this paper we propose a new probabilistic relaxation framework to perform robust multiple motion estimation and segmentation from a sequence of images. Our approach uses displa...
Alexander Strehl, Jake K. Aggarwal