DocumentCode
3022314
Title
A hierarchical classifier using new support vector machine
Author
Wang, Yu-Chiang ; Casasent, David
Author_Institution
Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA
fYear
2005
fDate
29 Aug.-1 Sept. 2005
Firstpage
851
Abstract
A binary hierarchical classifier is proposed to solve the multi-class classification problem. We also require rejection of non-target inputs, which produces 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 infrared data are excellent.
Keywords
Fourier transforms; pattern classification; support vector machines; Fourier transform; discrimination machine classifier; hierarchical SVRDM classifier; multiclass classification; support vector machine; support vector representation; Classification tree analysis; Face recognition; Fourier transforms; Neural networks; Pattern recognition; Support vector machine classification; Support vector machines; Target recognition; Testing; Voting;
fLanguage
English
Publisher
ieee
Conference_Titel
Document Analysis and Recognition, 2005. Proceedings. Eighth International Conference on
ISSN
1520-5263
Print_ISBN
0-7695-2420-6
Type
conf
DOI
10.1109/ICDAR.2005.16
Filename
1575665
Link To Document