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SDM
2009
SIAM
117views Data Mining» more  SDM 2009»
14 years 4 months ago
Spatially Cost-Sensitive Active Learning.
In active learning, one attempts to maximize classifier performance for a given number of labeled training points by allowing the active learning algorithm to choose which points...
Alexander Liu, Goo Jun, Joydeep Ghosh
IJISMD
2010
135views more  IJISMD 2010»
13 years 4 months ago
On the Usage of Labels and Icons in Business Process Modeling
The value of business process models is dependent not only on the choice of graphical elements in the model, but also on their annotation with additional textual and graphical inf...
Jan Mendling, Jan Recker, Hajo A. Reijers
MICCAI
2002
Springer
14 years 8 months ago
Labeling the Brain Surface Using a Deformable Multiresolution Mesh
We propose to match a labeled mesh onto the patient brain surface in a multiresolution way for labeling the patient brain. Labeling the patient brain surface provides a map of the ...
Sylvain Jaume, Benoit M. Macq, Simon K. Warfield
CVPR
2012
IEEE
11 years 10 months ago
Structured Local Predictors for image labelling
In this paper we introduce Structured Local Predictors (SLP) – A new formulation that considers the image labelling problem from a structured learning point of view. SLP are loc...
Samuel Rota Bulò, Peter Kontschieder, Marce...
AAIM
2008
Springer
142views Algorithms» more  AAIM 2008»
13 years 9 months ago
Engineering Label-Constrained Shortest-Path Algorithms
We consider a generalization of the shortest-path problem: given an alphabet , a graph G whose edges are weighted and -labeled, and a regular language L , the L-constrained shortes...
Christopher L. Barrett, Keith R. Bisset, Martin Ho...