Sciweavers

1297 search results - page 24 / 260
» Covariant Derivatives and Vision
Sort
View
ICASSP
2011
IEEE
13 years 1 months ago
Multiantenna detection under noise uncertainty and primary user's spatial structure
Spectrum sensing is a challenging key component of the Cognitive Radio paradigm, since primary signals must be detected in the face of noise uncertainty and at signal-to-noise rat...
David Ramírez, Gonzalo Vazquez-Vilar, Rober...
PAMI
2007
129views more  PAMI 2007»
13 years 9 months ago
Algorithmic Differentiation: Application to Variational Problems in Computer Vision
Abstract— Many vision problems can be formulated as minimization of appropriate energy functionals. These energy functionals are usually minimized, based on the calculus of varia...
Thomas Pock, Michael Pock, Horst Bischof
BMCV
2000
Springer
14 years 2 months ago
Front-End Vision: A Multiscale Geometry Engine
The paper is a short tutorial on the multiscale differential geometric possibilities of the front-end visual receptive fields, modeled by Gaussian derivative kernels. The paper is ...
Bart M. ter Haar Romeny, Luc Florack
ICPR
2000
IEEE
14 years 10 months ago
Reduction of Bias in Maximum Likelihood Ellipse Fitting
An improved maximum likelihood estimator for ellipse fitting based on the heteroscedastic errors-in-variables (HEIV) regression algorithm is proposed. The technique significantly ...
Bogdan Matei, Peter Meer
ICPR
2000
IEEE
14 years 10 months ago
General Bias/Variance Decomposition with Target Independent Variance of Error Functions Derived from the Exponential Family of D
An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...
Jakob Vogdrup Hansen, Tom Heskes