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IJCAI
2007
13 years 7 months ago
A Subspace Kernel for Nonlinear Feature Extraction
Kernel based nonlinear Feature Extraction (KFE) or dimensionality reduction is a widely used pre-processing step in pattern classification and data mining tasks. Given a positive...
Mingrui Wu, Jason D. R. Farquhar
ICARCV
2008
IEEE
154views Robotics» more  ICARCV 2008»
13 years 12 months ago
Detecting spurious features using parity space
—Detection of spurious features is instrumental in many computer vision applications. The standard approach is feature based, where extracted features are matched between the ima...
David Törnqvist, Thomas B. Schön, Fredri...
SC
2005
ACM
13 years 11 months ago
Intelligent Feature Extraction and Tracking for Visualizing Large-Scale 4D Flow Simulations
Terascale simulations produce data that is vast in spatial, temporal, and variable domains, creating a formidable challenge for subsequent analysis. Feature extraction as a data r...
Fan-Yin Tzeng, Kwan-Liu Ma
ICML
2008
IEEE
14 years 6 months ago
Dirichlet component analysis: feature extraction for compositional data
We consider feature extraction (dimensionality reduction) for compositional data, where the data vectors are constrained to be positive and constant-sum. In real-world problems, t...
Hua-Yan Wang, Qiang Yang, Hong Qin, Hongbin Zha
ICPR
2002
IEEE
13 years 10 months ago
Hand Pose Recognition Using Curvature Scale Space
In this paper, we present a novel feature extraction approach based on Curvature Scale Space (CSS) for translation, scale, and rotation invariant recognition of hand poses. First,...
Chin-Chen Chang, I-Yen Chen, Yea-Shuan Huang