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» Feature Mining for Image Classification
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ICDM
2009
IEEE
137views Data Mining» more  ICDM 2009»
15 years 9 months ago
Regression Learning Vector Quantization
— Learning Vector Quantization (LVQ) is a popular class of nearest prototype classifiers for multiclass classification. Learning algorithms from this family are widely used becau...
Mihajlo Grbovic, Slobodan Vucetic
124
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ICML
2007
IEEE
16 years 3 months ago
Self-taught learning: transfer learning from unlabeled data
We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin ...
97
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CVPR
2003
IEEE
16 years 4 months ago
Kullback-Leibler Boosting
In this paper, we develop a general classification framework called Kullback-Leibler Boosting, or KLBoosting. KLBoosting has following properties. First, classification is based o...
Ce Liu, Heung-Yeung Shum
124
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INCDM
2010
Springer
146views Data Mining» more  INCDM 2010»
15 years 6 months ago
Learning from Humanoid Cartoon Designs
Abstract. Character design is a key ingredient to the success of any comicbook, graphic novel, or animated feature. Artists typically use shape, size and proportion as the first de...
Md. Tanvirul Islam, Kaiser Md. Nahiduzzaman, Why Y...
131
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CIARP
2006
Springer
15 years 6 months ago
Automatic Band Selection in Multispectral Images Using Mutual Information-Based Clustering
Feature selection and dimensionality reduction are crucial research fields in pattern recognition. This work presents the application of a novel technique on dimensionality reducti...
Adolfo Martínez Usó, Filiberto Pla, ...