Principal
component analysis is a technique used in
statistical pattern
recognition for data
reduction and feature extraction. As the pattern
mostly contain redundant in... AlgorithmMatlab
Fast facial feature extraction algorithm KPCA, than ordinary PCA feature extraction algorithm in the efficiency of a good many... Special EffectsMatlab
Sometimes, we run into a situation when we badly need to hook some Kernel function, but are unable to do it via conventional PE-based hooking. This article explains how Kernel functions can be directly hooked. As a sample project, we are going to present a removable USB storage device as a basic dis... Windows KernelOthers
PCA-SIFT invariant image feature extraction, using principal component analysis extracted SIFT features, improved efficiency.... Special EffectsVisual C++
Which contains the principal component analysis PCA of the Matlab code, including the extraction of the main element, seeking variance contribution rate, contribution rate of histogram mapping, etc.... matlabMatlab
KPCA major noise in the image to have the application. In addition can also be used for feature extraction, dimensionality reduction using... Special EffectsMatlab