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
fDate :
29 Aug.-1 Sept. 2005
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;
Conference_Titel :
Document Analysis and Recognition, 2005. Proceedings. Eighth International Conference on
Print_ISBN :
0-7695-2420-6
DOI :
10.1109/ICDAR.2005.16