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» On learning with dissimilarity functions
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CIE
2007
Springer
14 years 3 months ago
Input-Dependence in Function-Learning
In the standard model of inductive inference, a learner gets as input the graph of a function, and has to discover (in the limit) a program for the function. In this paper, we cons...
Sanjay Jain, Eric Martin, Frank Stephan
CVPR
2009
IEEE
15 years 4 months ago
Global Optimization for Alignment of Generalized Shapes
In this paper, we introduce a novel algorithm to solve global shape registration problems. We use gray-scale “images” to represent source shapes, and propose a novel twocompo...
Hongsheng Li (Lehigh University), Tian Shen (Lehig...
CIARP
2003
Springer
14 years 2 months ago
Fast Handwritten Recognition Using Continuous Distance Transformation
The Continuous Distance Transformation (CDT) used in conjunction with a k-NN classifier has been shown to provide good results in the task of handwriting recognition [1]. Unfortun...
Joaquim Arlandis, Juan Carlos Pérez-Cortes
PAMI
2006
226views more  PAMI 2006»
13 years 9 months ago
Graph Partitioning Active Contours (GPAC) for Image Segmentation
In this paper we introduce new type of variational segmentation cost functions and associated active contour methods that are based on pairwise similarities or dissimilarities of t...
Baris Sumengen, B. S. Manjunath
ICCV
2009
IEEE
13 years 6 months ago
Kernel map compression using generalized radial basis functions
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
Omar Arif, Patricio A. Vela