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» Unsupervised Learning of Image Transformations
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TIP
2002
179views more  TIP 2002»
14 years 11 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
ICMCS
2005
IEEE
152views Multimedia» more  ICMCS 2005»
15 years 5 months ago
Texture-Based Remote-Sensing Image Segmentation
Typically, high-resolution remote sensing (HRRS) images contain a high level noise as well as possess different texture scales. As a result, existing image segmentation approaches...
Dihua Guo, Vijayalakshmi Atluri, Nabil R. Adam
PAMI
2011
14 years 6 months ago
Multiple Kernel Learning for Dimensionality Reduction
—In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. The resulting ...
Yen-Yu Lin, Tyng-Luh Liu, Chiou-Shann Fuh
ALT
2006
Springer
15 years 8 months ago
Unsupervised Slow Subspace-Learning from Stationary Processes
Abstract. We propose a method of unsupervised learning from stationary, vector-valued processes. A low-dimensional subspace is selected on the basis of a criterion which rewards da...
Andreas Maurer
IJAR
2006
197views more  IJAR 2006»
14 years 11 months ago
Rough fuzzy set based scale space transforms and their use in image analysis
In this paper we present a multi-scale method based on the hybrid notion of rough fuzzy sets, coming from the combination of two models of uncertainty like vagueness by handling r...
Alfredo Petrosino, Giuseppe Salvi