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libsvm-2.81.tar
- 模式识别中的支撑向量机,可用于人脸识别训练!-pattern recognition of Support Vector Machines can be used for face recognition training!
libsvm-mat-2.81-1
- 支撑向量机库libsvm与matlab的接口,可以连接在matlab中做实验!-Support Vector Machine for libsvm with Matlab interface can be connected to the experimental Matlab do!
PlotText
- 一个将文字变成矢量的JAVA程序,用于CAD中绘图仪的输出-words into a vector JAVA procedures for CAD plotter output
200611743011276_daimaz.com
- 本代码实现的是windows的矢量字库的读写,生成8*8字模-the source implementation of the windows vector font reader, generate 8 * 8 Fonts
ras2vec_2
- 国际上开源的矢量化算法，速度堪比R2V软件-international revenue vector algorithm, the speed guaranteed under Application of the R2V software
SVM(matlab)
- 支持向量机(SVM)实现的分类算法源码[matlab] -Support Vector Machine (SVM), a classification algorithm source code [Matlab]
jianliyangben
- 一个基于BP神经网络的matlab程序，可以实现对几种字体0-9的数字识别，这个文件是建立样本矢量的压缩包。-a neural network based on BP's Matlab procedures, Some can be achieved on the font 0 -9 identification number, the document is to establish the sample vector compressed.
SVG_Export_of_Figures
- Converts 3D and 2D MATLAB plots to the scalable vector format (SVG).-Converts 2D and 3D plots to the MATLAB scala ble vector format (SVG).
XMathLib
- XMathLib是一个通用的3D图形数学库。 其中包含两个部分： XMathLib和XGeomLib。分别处理数学和几何运算。 数学部分包含向量、矩阵、四元数的运算。以及其它的运算。 几何部分包含Box Frustum AABB OBB Ray Line Line-Segment Plan Triangle等的运算。-XMathLib is a generic 3D graphics math. Which consists of two parts : XMathLib and
wzsb
- 文字识别系统--数字字符的识别算法，将数字字符的顶部、左右两侧的局部轮廓结构和统计特征组合成特征向量，用以描述10个数字。采用用结构语句识别算法识别底部残缺的和完整的数字字符。-Character Recognition System -- Character recognition algorithm, the top figures of characters, around both sides of the partial outline of the structure and sta
20070604141700
- 源码提供了矢量字库轮廓的提取,为后续的汉字的识别打下了良好的基础.-source provided a vector font outline of the extraction, for the follow-up character recognition lay a good foundation.
OpenCV_face_detector
- This zip file contains source code and windows executables for carrying out face detection on a gray scale image. The code implements Viola-Jones adaboosted algorithm for face detection by providing a mex implementation of OpenCV s face detector. Ins
基于支持向量机的手写体相似字识别
- 一种基于支持向量机的手写体相似字识别方法，很有参考意义（维普浏览器）-based on support vector machines similar to the handwritten word recognition methods of great reference significance (Wei-pu browser)
K-means算法源码
- kmeans This directory contains code implementing the K-means algorithm. Source code may be found in KMEANS.CPP. Sample data isfound in KM2.DAT. The KMEANS program accepts input consisting of vectors and calculates the given number of cluster centers
gabor_svm
- 采用Gabor_Palm函数提取掌纹图像的能量特征，并将得到的结果分块，分别计算每块的均值和方差作为特征向量。特征向量的长度为160.-Gabor_Palm function using the energy extracted palmprint image features, and will be the result of sub-blocks, each block were calculated the mean and variance as a feature vector
dfbrec_l
- DFBREC_L Directional Filterbank Reconstruction using Ladder Structure x = dfbrec_l(y, fname) Input: y: subband images in a cell vector of length 2^n f: filter in the ladder network structure, can be a string naming a stan
backsamp
- BACKSAMP Backsampling the subband images of the directional filter bank y = backsamp(y) Input and output are cell vector of dyadic length This function is called at the end of the DFBDEC to obtain subband images with overall
Face-Detection
- 完整的包括皮肤及动作识别的C++人脸检测源代码，涉及的技术有：小波分析，尺度缩减模型（PCA,LDA,ICA），人工神经网络（ANN），支持向量机（SVM），SSE编程，图像处理，直方图均衡，图像滤波，C++编程等。-Complete, including skin and actions identified C++ face detection source code, the technology involved are: wavelet analysis, scaling down m
fsvmPpca-face-Recognition
- 首先用PCA对ORA人脸图像降维，然后用模糊支持向量机对提取的特征向量进行分类，识别率较高。-First using PCA for dimensionality reduction ORA face image, and then use fuzzy support vector machine to classify the extracted feature vectors, the recognition rate is higher.
support-vector-machine
- 本书主要以分类问题（模式识别，判别分析）和回归问题为背景，系统阐述支持向量机和相应的优化算法-This book mainly classification (pattern recognition, discriminant analysis) and regression as the background, the system describes support vector machine and the corresponding optimization