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» A data driven method for feature transformation
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NN
2000
Springer
161views Neural Networks» more  NN 2000»
13 years 7 months ago
How good are support vector machines?
Support vector (SV) machines are useful tools to classify populations characterized by abrupt decreases in density functions. At least for one class of Gaussian data model the SV ...
Sarunas Raudys
IJCNLP
2004
Springer
14 years 1 months ago
A Study of Semi-discrete Matrix Decomposition for LSI in Automated Text Categorization
Abstract. This paper proposes the use of Latent Semantic Indexing (LSI) techniques, decomposed with semi-discrete matrix decomposition (SDD) method, for text categorization. The SD...
Qiang Wang, Xiaolong Wang, Guan Yi

Publication
307views
14 years 1 months ago
Scale and Rotation Invariant Detection of Singular Patterns in Vector Flow Fields
We present a method for detecting and describing features in vector flow fields. Our method models flow fields locally using a linear combination of complex monomials. These monomi...
Wei Liu, Eraldo Ribeiro
PAMI
2007
152views more  PAMI 2007»
13 years 7 months ago
DCT-Based Iris Recognition
—This paper presents a novel iris coding method based on differences of discrete cosine transform (DCT) coefficients of overlapped angular patches from normalized iris images. Th...
Donald M. Monro, Soumyadip Rakshit, Dexin Zhang
MCS
2004
Springer
14 years 1 months ago
Multiple Classifiers System for Reducing Influences of Atypical Observations
Atypical observations, which are called outliers, are one of difficulties to apply standard Gaussian density based pattern classification methods. Large number of outliers makes di...
Sarunas Raudys, Masakazu Iwamura