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» Risk sensitive robust support vector machines
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ACIVS
2005
Springer
14 years 1 months ago
Object Recognition Using Local Characterisation and Zernike Moments
Abstract. Even if lots of object invariant descriptors have been proposed in the literature, putting them into practice in order to obtain a robust system face to several perturbat...
Anant Choksuriwong, Hélène Laurent, ...
AVSS
2006
IEEE
13 years 11 months ago
Classification-Based Likelihood Functions for Bayesian Tracking
The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...
Chunhua Shen, Hongdong Li, Michael J. Brooks
CCECE
2006
IEEE
13 years 11 months ago
A Simplified Early Auditory Model with Application in Speech/Music Classification
The past decade has seen extensive research on audio classification and segmentation algorithms. However, the effect of background noise on the performance of classification has n...
Wei Chu, Benoît Champagne
ICCV
2003
IEEE
14 years 9 months ago
Recognition with Local Features: the Kernel Recipe
Recent developments in computer vision have shown that local features can provide efficient representations suitable for robust object recognition. Support Vector Machines have be...
Christian Wallraven, Barbara Caputo, Arnulf B. A. ...
IPMI
2003
Springer
14 years 8 months ago
Feature Selection for Shape-Based Classification of Biological Objects
Abstract. In this paper, feature selection methodology from the machine learning literature is applied to the problem of shape-based classification. This methodology discards stati...
Paul A. Yushkevich, Sarang C. Joshi, Stephen M. Pi...