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SAC
2008
ACM
13 years 3 months ago
Using the RRT algorithm to optimize classification systems for handwritten digits and letters
Multi-objective genetic algorithms have been often used to optimize classification systems, but little is discussed on their computational cost to solve such problems. This paper ...
Paulo Vinicius Wolski Radtke, Robert Sabourin, Ton...
ICDAR
2011
IEEE
12 years 3 months ago
Tuning between Exponential Functions and Zones for Membership Functions Selection in Voronoi-Based Zoning for Handwritten Charac
— In Handwritten Character Recognition, zoning is rigtly considered as one of the most effective feature extraction techniques. In the past, many zoning methods have been propose...
Sebastiano Impedovo, Giuseppe Pirlo
CIKM
2008
Springer
13 years 5 months ago
Learning a two-stage SVM/CRF sequence classifier
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Guilherme Hoefel, Charles Elkan
PAMI
2012
11 years 6 months ago
Task-Driven Dictionary Learning
—Modeling data with linear combinations of a few elements from a learned dictionary has been the focus of much recent research in machine learning, neuroscience, and signal proce...
Julien Mairal, Francis Bach, Jean Ponce
ICDAR
2007
IEEE
13 years 10 months ago
Multi-Objective Optimization for SVM Model Selection
In this paper, we propose a multi-objective optimization method for SVM model selection using the well known NSGA-II algorithm. FA and FR rates are the two criteria used to find ...
Clément Chatelain, Sébastien Adam, Y...