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» Image Classification Using Marginalized Kernels for Graphs
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ICPR
2010
IEEE
13 years 11 months ago
Kernel-Based Implicit Regularization of Structured Objects
Weighted graph regularization provides a rich framework that allows to regularize functions defined over the vertices of a weighted graph. Until now, such a framework has been only...
François-Xavier Dupé, Sébastien Bougleux, Luc B...
ICCV
2011
IEEE
12 years 7 months ago
A Graph-matching Kernel for Object Categorization
This paper addresses the problem of category-level image classification. The underlying image model is a graph whose nodes correspond to a dense set of regions, and edges reflec...
Olivier Duchenne, Armand Joulin, Jean Ponce
ICIAP
2003
ACM
14 years 8 months ago
Old fashioned state-of-the-art image classification
In this paper we present a statistical learning scheme for image classification based on a mixture of old fashioned ideas and state of the art learning tools. We represent input i...
Annalisa Barla, Francesca Odone, Alessandro Verri
TR
2010
204views Hardware» more  TR 2010»
13 years 2 months ago
Anomaly Detection Through a Bayesian Support Vector Machine
This paper investigates the use of a one-class support vector machine algorithm to detect the onset of system anomalies, and trend output classification probabilities, as a way to ...
Vasilis A. Sotiris, Peter W. Tse, Michael Pecht
ICML
2004
IEEE
14 years 8 months ago
Boosting margin based distance functions for clustering
The performance of graph based clustering methods critically depends on the quality of the distance function, used to compute similarities between pairs of neighboring nodes. In t...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall