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DAGM
2008
Springer
15 years 8 months ago
Boosting for Model-Based Data Clustering
In this paper a novel and generic approach for model-based data clustering in a boosting framework is presented. This method uses the forward stagewise additive modeling to learn t...
Amir Saffari, Horst Bischof
ICIP
2003
IEEE
16 years 8 months ago
Pixel classification through divergence-based integration of texture methods with conflict resolution
This paper presents a new technique for combining multiple texture feature extraction methods in order to classify the pixels of an input image into a set of texture models of int...
Domènec Puig, Miguel Angel García
ACL
1998
15 years 8 months ago
Combination of an Automatic and an Interactive Disambiguation Method
In natural language processing, many methods have been proposed to solve the ambiguity problems. In this paper, we propose a technique to combine a method of interactive disambigu...
Masaya Yamaguchi, Takeyuki Kojima, Nobuo Inui, Yos...
ICIP
2010
IEEE
15 years 4 months ago
A new subspace learning method in Fourier domain for texture classification
This paper proposes a new texture classification approach. There are two main contributions in the proposed method. First, input texture images are transformed to the composite Fo...
Shu Liao, Albert C. S. Chung
ICML
2006
IEEE
16 years 7 months ago
Sequential update of ADtrees
Ingcreasingly, data-mining algorithms must deal with databases that continuously grow over time. These algorithms must avoid repeatedly scanning their databases. When database att...
Josep Roure, Andrew W. Moore