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JCP
2008
167views more  JCP 2008»
14 years 10 months ago
Accelerated Kernel CCA plus SVDD: A Three-stage Process for Improving Face Recognition
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
Ming Li, Yuanhong Hao
VIS
2008
IEEE
135views Visualization» more  VIS 2008»
15 years 11 months ago
Interactive Volume Exploration for Feature Detection and Quantification in Industrial CT Data
This paper presents a novel method for interactive exploration of industrial CT volumes such as cast metal parts, with the goal of interactively detecting, classifying, and quantif...
Markus Hadwiger, Laura Fritz, Christof Rezk-Sala...
TNN
2008
74views more  TNN 2008»
14 years 10 months ago
Pattern Representation in Feature Extraction and Classifier Design: Matrix Versus Vector
The matrix, as an extended pattern representation to the vector, has proven to be effective in feature extraction. But the subsequent classifier following the matrix-pattern-orien...
Zhe Wang, Songcan Chen, Jun Liu, Daoqiang Zhang
IVC
2008
147views more  IVC 2008»
14 years 10 months ago
Distinctive and compact features
We consider the problem of extracting features for multi-class recognition problems. The features are required to make fine distinction between similar classes, combined with tole...
Ayelet Akselrod-Ballin, Shimon Ullman
BMCBI
2008
160views more  BMCBI 2008»
14 years 10 months ago
Feature selection environment for genomic applications
Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e....
Fabrício Martins Lopes, David Correa Martin...