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» Learning Low-Level Vision
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ECCV
2006
Springer
14 years 10 months ago
Riemannian Manifold Learning for Nonlinear Dimensionality Reduction
In recent years, nonlinear dimensionality reduction (NLDR) techniques have attracted much attention in visual perception and many other areas of science. We propose an efficient al...
Tony Lin, Hongbin Zha, Sang Uk Lee
ECCV
2000
Springer
14 years 10 months ago
Unsupervised Learning of Models for Recognition
We present a method to learn object class models from unlabeled and unsegmented cluttered scenes for the purpose of visual object recognition. We focus on a particular type of mode...
Markus Weber, Max Welling, Pietro Perona
ICPR
2004
IEEE
14 years 10 months ago
Hierarchical Object Indexing and Sequential Learning
This work is about scene interpretation in the sense of detecting and localizing instances from multiple object classes. We concentrate on object indexing: generate an over-comple...
Donald Geman, Xiaodong Fan
ICPR
2004
IEEE
14 years 10 months ago
Learning High-level Independent Components of Images through a Spectral Representation
Statistical methods, such as independent component analysis, have been successful in learning local low-level features from natural image data. Here we extend these methods for le...
Aapo Hyvärinen, Jussi T. Lindgren
ICPR
2004
IEEE
14 years 10 months ago
A Probabilistic Approach to Learning Costs for Graph Edit Distance
Graph edit distance provides an error-tolerant way to measure distances between attributed graphs. The effectiveness of edit distance based graph classification algorithms relies ...
Horst Bunke, Michel Neuhaus