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» Using Random Forests for Handwritten Digit Recognition
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ICDAR
2007
IEEE
13 years 11 months ago
Using Random Forests for Handwritten Digit Recognition
In the Pattern Recognition field, growing interest has been shown in recent years for Multiple Classifier Systems and particularly for Bagging, Boosting and Random Subspaces. Th...
Simon Bernard, Sébastien Adam, Laurent Heut...
SSPR
2004
Springer
13 years 10 months ago
Feature Subset Selection Using an Optimized Hill Climbing Algorithm for Handwritten Character Recognition
This paper presents an optimized Hill Climbing algorithm to select a subset of features for handwritten character recognition. The search is conducted taking into account a random ...
Carlos M. Nunes, Alceu de Souza Britto Jr., Celso ...
ICIP
2010
IEEE
13 years 2 months ago
Building Emerging Pattern (EP) Random forest for recognition
The Random forest classifier comes to be the working horse for visual recognition community. It predicts the class label of an input data by aggregating the votes of multiple tree...
Liang Wang, Yizhou Wang, Debin Zhao
DMIN
2006
164views Data Mining» more  DMIN 2006»
13 years 6 months ago
Random Forest and PCA for Self-Organizing Maps based Automatic Music Genre Discrimination
Digital music distribution industry has seen a tremendous growth in resent years. Tasks such us automatic music genre discrimination address new and exciting research challenges. A...
Xin Jin, Rongfang Bie
FUZZY
2001
Springer
184views Fuzzy Logic» more  FUZZY 2001»
13 years 9 months ago
Handwritten Digit Recognition: A Neural Network Demo
Abstract. A handwritten digit recognition system was used in a demonstration project to visualize artificial neural networks, in particular Kohonen’s self-organizing feature map...
Berend-Jan van der Zwaag