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» Visualizing Weighted Edges in Graphs
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CVPR
2006
IEEE
16 years 1 months ago
Graph Laplacian Kernels for Object Classification from a Single Example
Classification with only one labeled example per class is a challenging problem in machine learning and pattern recognition. While there have been some attempts to address this pr...
Hong Chang, Dit-Yan Yeung
SCIA
2007
Springer
119views Image Analysis» more  SCIA 2007»
15 years 5 months ago
Watertight Multi-view Reconstruction Based on Volumetric Graph-Cuts
This paper proposes a fast 3D reconstruction approach for efficiently generating watertight 3D models from multiple short baseline views. Our method is based on the combination of...
Mario Sormann, Christopher Zach, Joachim Bauer, Ko...
SIAMDM
2008
119views more  SIAMDM 2008»
14 years 11 months ago
On the Graph Bisection Cut Polytope
Given a graph G = (V, E) with node weights v N {0}, v V , and some number F N{0}, the convex hull of the incidence vectors of all cuts (S), S V with (S) F and (V \ S) F is ...
Michael Armbruster, Christoph Helmberg, Marzena F&...
ICCV
2009
IEEE
1714views Computer Vision» more  ICCV 2009»
16 years 4 months ago
Power watersheds: a new image segmentation framework extending graph cuts, random walker and optimal spanning forest
In this work, we extend a common framework for seeded image segmentation that includes the graph cuts, ran- dom walker, and shortest path optimization algorithms. Viewing an ima...
Camille Couprie, Leo Grady, Laurent Najman, Hugues...
ICML
2006
IEEE
15 years 12 months ago
An analysis of graph cut size for transductive learning
I consider the setting of transductive learning of vertex labels in graphs, in which a graph with n vertices is sampled according to some unknown distribution; there is a true lab...
Steve Hanneke