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» Nonlinear Nonnegative Component Analysis
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NIPS
2008
13 years 9 months ago
Robust Kernel Principal Component Analysis
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
Minh Hoai Nguyen, Fernando De la Torre
SGAI
2005
Springer
14 years 1 months ago
The Effect of Principal Component Analysis on Machine Learning Accuracy with High Dimensional Spectral Data
This paper presents the results of an investigation into the use of machine learning methods for the identification of narcotics from Raman spectra. The classification of spectr...
Tom Howley, Michael G. Madden, Marie-Louise O'Conn...
WACV
2008
IEEE
14 years 2 months ago
Object Categorization Based on Kernel Principal Component Analysis of Visual Words
In recent years, many researchers are studying object categorization problem. It is reported that bag of keypoints approach which is based on local features without topological in...
Kazuhiro Hotta
FSE
2005
Springer
85views Cryptology» more  FSE 2005»
14 years 1 months ago
Analysis of the Non-linear Part of Mugi
This paper presents the results of a preliminary analysis of the stream cipher Mugi. We study the nonlinear component of this cipher and identify several potential weaknesses in it...
Alex Biryukov, Adi Shamir
ICIP
2004
IEEE
14 years 9 months ago
Advances in texture analysis-energy dominant component & multiple hypothesis testing
Modelling textured images as AM-FM functions has been applied during the last years to texture analysis and segmentation tasks. In this paper we present some advances in two direc...
Iasonas Kokkinos, Georgios Evangelopoulos, Petros ...