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Dimension-reduction--toolbox
- 该工具箱中包含了多种降维算法。其中有传统的PCA和Local PCA算法，也有典型的流形学习算法，如Isomap、LLE、HLLE、Laplacian Eigenmaps 和 Local Tangent Space 。-The toolbox contains a variety of dimensionality reduction algorithms. In which the traditional PCA and Local PCA algorithms, there are the
drtoolbox.tar
- 这是一个MATLAB工具箱包括32个降维程序，主要包括 pca,lda,MDS等十几个程序包，对于图像处理非常具有参考价值- ，This Matlab toolbox implements 32 techniques for dimensionality reduction. These techniques are all available through the COMPUTE_MAPPING function or trhough the GUI. The following techn
Palm-biometrics-using-UDP
- This paper develops an efficient classification algorithm called UDP, which reduces the high dimension of sample to low dimensional subspace simply said as dimensionality reduction.UDP takes into account both the local and non-local quantities. It ca
sift
- 1 SIFT 发展历程 SIFT算法由D.G.Lowe 1999年提出，2004年完善总结。后来Y.Ke将其描述子部分用PCA代替直方图的方式，对其进行改进。 2 SIFT 主要思想 SIFT算法是一种提取局部特征的算法，在尺度空间寻找极值点，提取位置，尺度，旋转不变量。 3 SIFT算法的主要特点： a) SIFT特征是图像的局部特征，其对旋转、尺度缩放、亮度变化保持不变性，对视角变化、仿射变换、噪声也保持一定程度的稳定性。 b) 独特性(Distinctive
CodesaImages
- 用于指纹检测等，利用图像的梯度方向，获得局部主导方向。Principal Component Analysis （PCA），包含有高斯金字塔分层，SVD奇异值分解，内含测试图像-Used for fingerprint detection, etc. Using the gradient direction of image to get local leading direction. Principal Component Analysis (PCA), contains a gaussi
drtoolbox
- Matlab针对各种数据预处理的降维方法，源码集合。-Currently, the Matlab Toolbox for Dimensionality Reduction contains the following techniques: Principal Component Analysis (PCA) Probabilistic PCA Factor Analysis (FA) Sammon mapping Lin
LBPandPCA
- 为有效解决局部二元模式(LBP)在人脸识别特征提取时维数过高的问题，提出了一种结合LBP特征和主成分分析(PCA)的人脸识别方法．-To effectively solve the local binary pattern (LBP) feature extraction in face recognition problem of high dimensionality, we propose a combination of LBP features and principal compon
06701687
- The ear, as a biometric, has been given less attention, compared to other biometrics such as fingerprint, face and iris. Since it is a relatively new biometric, no commercial applications involving ear recognition are available. Intensive
drtoolbox.tar
- 用于降维的matlab工具包，包括PCA，LDA，LLE，等-Matlab Toolbox for Dimensionality Reduction Principal Component Analysis (PCA) Probabilistic PCA Factor Analysis (FA) Classical multidimensional scaling (MDS) Sammon mapping Linear Discriminant Analysis (LDA
pcasift-0.91nd.tar
- PCA-SIFT:一个更独特的为当地的图像描述符表示-PCA-SIFT: A More Distinctive Representation for Local Image Descr iptors
pca-sift
- 具有含有最近年的改进sift研究文献，有便于深入了解局部特征研究领域-containing the research of modified sift local features, have benefit to deep learning the research field