loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Eighth International Conference on Document Analysis and Recognition (ICDAR'05)
A Hierarchical Classifier Using New Support Vector Machine
Seoul, Korea
August 31-September 01
ISBN: 0-7695-2420-6
Yu-Chiang Wang, Carnegie Mellon University, Pittsburgh, PA
David Casasent, Carnegie Mellon University, Pittsburgh, PA
A binary hierarchical classifier is proposed to solve the multi-class classification problem. We also require rejection of non-target inputs, which thus producing a very difficult problem. The SVRDM (support vector representation and discrimination machine) classifier is considered at each node in the hierarchy, since it offers good generalization and rejection ability. Using this hierarchical SVRDM classifier with magnitude Fourier transform features, initial recognition and rejection test results on simulated infra-red data are excellent.
Citation:
Yu-Chiang Wang, David Casasent, "A Hierarchical Classifier Using New Support Vector Machine," icdar, pp.851-855, Eighth International Conference on Document Analysis and Recognition (ICDAR'05), 2005
Usage of this product signifies your acceptance of the Terms of Use.