Technical Program

Paper Detail

Paper:MLSP-P5.2
Session:Image and Video Processing
Time:Thursday, May 20, 13:00 - 15:00
Presentation: Poster
Topic: Machine Learning for Signal Processing: Image and Video Processing Applications
Title: MODIFIED KERNEL-BASED NONLINEAR FEATURE EXTRACTION
Authors: Guang Dai; Zhejiang University 
 Yuntao Qian; Zhejiang University 
 Sen Jia; Zhejiang University 
Abstract: Feature extraction techniques are widely used in many applications to pro-process data in order to reduce the complexity of subsequent processes. A group of kernel-based nonlinear Fisher discrminant analysis (KFDA) has attracted much attention due to their high performance. In this paper, the inherent limitations of those KFDA algorithms have been discussed and the novel algorithm will be proposed to effectively overcome those limitations. Experimental results on the face recognition suggest that this proposed algorithm is superior to the existing methods in terms of correct classification rate.
 
           Back


Home -||- Organizing Committee -||- Technical Committee -||- Technical Program -||- Plenaries
Paper Submission -||- Special Sessions -||- ITT -||- Paper Review -||- Exhibits -||- Tutorials
Information -||- Registration -||- Travel Insurance -||- Housing -||- Workshops

©2015 Conference Management Services, Inc. -||- email: webmaster@icassp2004.org -||- Last updated Wednesday, April 07, 2004