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135
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NIPS
2008
15 years 4 months ago
Learning Taxonomies by Dependence Maximization
We introduce a family of unsupervised algorithms, numerical taxonomy clustering, to simultaneously cluster data, and to learn a taxonomy that encodes the relationship between the ...
Matthew B. Blaschko, Arthur Gretton
SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
15 years 4 months ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava
149
Voted
ICIP
2007
IEEE
16 years 4 months ago
A Multi-Layer MRF Model for Object-Motion Detection in Unregistered Airborne Image-Pairs
In this paper, we give a probabilistic model for automatic change detection on airborne images taken with moving cameras. To ensure robustness, we adopt an unsupervised coarse mat...
Csaba Benedek, Tamas Sziranyi, Zoltan Kato, and Jo...
141
Voted
ICIP
2001
IEEE
16 years 4 months ago
Similarity measure for CCITT Group 4 compressed document images
Similarity measure of document images acts a crucial role in the area of document image retrieval. A method of measuring the similarity of CCITT Group 4 compressed document images...
Yue Lu, Chew Lim Tan, Liying Fan, Weihua Huang
98
Voted
ISCIS
2003
Springer
15 years 7 months ago
Comparison of Feature Sets Using Multimedia Translation
Feature selection is very important for many computer vision applications. However, it is hard to find a good measure for the comparison. In this study, feature sets are compared ...
Pinar Duygulu, Özge Can Özcanli, Norman ...