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TIP
2002
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13 years 8 months ago
Unsupervised image classification, segmentation, and enhancement using ICA mixture models
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...
Te-Won Lee, Michael S. Lewicki
ICTAI
1992
IEEE
14 years 26 days ago
Genetic Algorithms as a Tool for Feature Selection in Machine Learning
This paper describes an approach being explored to improve the usefulness of machine learning techniques for generating classification rules for complex, real world data. The appr...
Haleh Vafaie, Kenneth A. De Jong
CVPR
2003
IEEE
14 years 10 months ago
Kernel Principal Angles for Classification Machines with Applications to Image Sequence Interpretation
We consider the problem of learning with instances defined over a space of sets of vectors. We derive a new positive definite kernel f(A B) defined over pairs of matrices A B base...
Lior Wolf, Amnon Shashua
CVPR
2010
IEEE
14 years 5 months ago
A Generative Perspective on MRFs in Low-Level Vision
Markov random fields (MRFs) are popular and generic probabilistic models of prior knowledge in low-level vision. Yet their generative properties are rarely examined, while applica...
Uwe Schmidt, Qi Gao, Stefan Roth
ACCV
2006
Springer
13 years 10 months ago
Learning Multi-category Classification in Bayesian Framework
Abstract. We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat mult...
Atul Kanaujia, Dimitris N. Metaxas