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CVPR
2005
IEEE
16 years 9 months ago
Feature Kernel Functions: Improving SVMs Using High-Level Knowledge
Kernel functions are often cited as a mechanism to encode prior knowledge of a learning task. But it can be difficult to capture prior knowledge effectively. For example, we know ...
Qiang Sun, Gerald DeJong
ICPR
2008
IEEE
16 years 8 months ago
Preceding car tracking using belief functions and a particle filter
This article presents a preceding car rear view tracking algorithm which utilizes a particle filter and belief function data fusion. Most of tracking applications resort to only o...
Christèle Lecomte, John Klein, Pierre Mich&...
ICPR
2004
IEEE
16 years 8 months ago
Gaussian Energy Functions for Registration without Correspondences
A new criterion based on Gaussian fields is introduced and applied to the task of automatic rigid registration of point-sets. The method defines a simple energy function, which is...
Andreas Koschan, Besma R. Abidi, Faysal Boughorbel...
177
Voted
CIE
2007
Springer
16 years 1 months ago
Input-Dependence in Function-Learning
In the standard model of inductive inference, a learner gets as input the graph of a function, and has to discover (in the limit) a program for the function. In this paper, we cons...
Sanjay Jain, Eric Martin, Frank Stephan
IMR
2004
Springer
16 years 13 days ago
PDE-Based Gradient Limiting for Mesh Size Functions
We propose a new method for limiting the gradients in a mesh size function by solving a non-linear partial differential equation on the background mesh. Our gradient limiting Ham...
Per-Olof Persson