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» Image Classification Using Marginalized Kernels for Graphs
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GBRPR
2007
Springer
13 years 8 months ago
Image Classification Using Marginalized Kernels for Graphs
We propose in this article an image classification technique based on kernel methods and graphs. Our work explores the possibility of applying marginalized kernels to image process...
Emanuel Aldea, Jamal Atif, Isabelle Bloch
ICIAP
2009
ACM
13 years 2 months ago
Tree Covering within a Graph Kernel Framework for Shape Classification
Abstract. Shape classification using graphs and skeletons usually involves edition processes in order to reduce the influence of structural noise. However, edition distances can no...
François-Xavier Dupé, Luc Brun
CAIP
2009
Springer
210views Image Analysis» more  CAIP 2009»
13 years 8 months ago
Shape Classification Using a Flexible Graph Kernel
The medial axis being an homotopic transformation, the skeleton of a 2D shape corresponds to a planar graph having one face for each hole of the shape and one node for each junctio...
François-Xavier Dupé, Luc Brun
COLT
1998
Springer
13 years 8 months ago
Large Margin Classification Using the Perceptron Algorithm
We introduce and analyze a new algorithm for linear classification which combines Rosenblatt's perceptron algorithm with Helmbold and Warmuth's leave-one-out method. Like...
Yoav Freund, Robert E. Schapire
ICPR
2010
IEEE
13 years 7 months ago
Kernel on Graphs Based on Dictionary of Paths for Image Retrieval
Recent approaches of graph comparison consider graphs as sets of paths [6, 5]. Kernels on graphs are then computed from kernels on paths. A common strategy for graph retrieval is ...
Jean-Emmanuel Haugeard, Sylvie Philipp-Foliguet, P...