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» Discriminative Learning of Max-Sum Classifiers
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ICPR
2008
IEEE
14 years 11 months ago
SVMs, Gaussian mixtures, and their generative/discriminative fusion
We present a new technique that employs support vector machines and Gaussian mixture densities to create a generative/discriminative joint classifier. In the past, several approac...
Georg Heigold, Hermann Ney, Thomas Deselaers
IJDAR
2002
116views more  IJDAR 2002»
13 years 9 months ago
Performance evaluation of pattern classifiers for handwritten character recognition
Abstract. This paper describes a performance evaluation study in which some efficient classifiers are tested in handwritten digit recognition. The evaluated classifiers include a s...
Cheng-Lin Liu, Hiroshi Sako, Hiromichi Fujisawa
CVPR
2005
IEEE
14 years 12 months ago
Local Discriminant Embedding and Its Variants
We present a new approach, called local discriminant embedding (LDE), to manifold learning and pattern classification. In our framework, the neighbor and class relations of data a...
Hwann-Tzong Chen, Huang-Wei Chang, Tyng-Luh Liu
ICDAR
2009
IEEE
14 years 4 months ago
Unsupervised Selection and Discriminative Estimation of Orthogonal Gaussian Mixture Models for Handwritten Digit Recognition
The problem of determining the appropriate number of components is important in finite mixture modeling for pattern classification. This paper considers the application of an unsu...
Xuefeng Chen, Xiabi Liu, Yunde Jia
ECCV
2008
Springer
14 years 11 months ago
Multiple Component Learning for Object Detection
Abstract. Object detection is one of the key problems in computer vision. In the last decade, discriminative learning approaches have proven effective in detecting rigid objects, a...
Boris Babenko, Pietro Perona, Piotr Dollár,...