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» Combining SVM Classifiers for Handwritten Digit Recognition
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ICASSP
2011
IEEE
12 years 11 months ago
Maximum margin structure learning of Bayesian network classifiers
Recently, the margin criterion has been successfully used for parameter optimization in graphical models. We introduce maximum margin based structure learning for Bayesian network...
Franz Pernkop, Michael Wohlmay, Manfred Mücke
ICDAR
2003
IEEE
14 years 24 days ago
Optimizing Binary Feature Vector Similarity Measure using Genetic Algorithm and Handwritten Character Recognition
Classifying an unknown input is a fundamental problem in pattern recognition. A common method is to define a distance metric between patterns and find the most similar pattern i...
Sung-Hyuk Cha, Charles C. Tappert, Sargur N. Sriha...
ICDAR
2009
IEEE
13 years 5 months ago
A Feedback-Based Multi-Classifier System
Multi-classifier approach is a widespread strategy used in many difficult classification problems. Traditionally, in a multi-classifier approach, a classification decision based o...
Giuseppe Pirlo, Claudia Adamita Trullo, Donato Imp...
ICC
2007
IEEE
141views Communications» more  ICC 2007»
14 years 1 months ago
Accurate Classification of the Internet Traffic Based on the SVM Method
—The need to quickly and accurately classify Internet traffic for security and QoS control has been increasing significantly with the growing Internet traffic and applications ov...
Zhu Li, Ruixi Yuan, Xiaohong Guan
ICPR
2008
IEEE
14 years 8 months ago
Hybrid statistical-structural on-line Chinese character recognition with fuzzy inference system
In this paper, we propose an original hybrid statistical-structural method for on-line Chinese character recognition. We model characters thanks to fuzzy inference rules combining...
Éric Anquetil, Adrien Delaye, Sébast...