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搜索资源 - SVM face recognition
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基于pac的svm的MATLAB代码,可进行人脸识别,正确率较高-Pac of svm based MATLAB code, can be face recognition, high accuracy
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采用支持向量机算法编写的人脸识别程序,可以达到一定的精确度,适合初学者-Face recognition using svm algorithm
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利用支持向量机和PCA技术设计人脸识别系统,并作出GUI界面便于理解程序,同时增加可视化。并附带ORL人脸库-Face recognition system with GUI is easy to understand,designed based on SVM and PCA technologies. The file also has ORL face .
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基于pca和svm的人脸识别系统。gui图形交互界面的简单应用。-A face recognition system based on pca and SVM.The simple application of GUI graphical interface.
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基于SVM和PCA的人脸识别算法,有GUI界面,程序运行良好。-Based on SVM and PCA face recognition algorithm, GUI interface, the program works well.
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基于opencv3.0的SVM分类器源码(可直接运行),在人脸识别类的领域。-Based on the SVM classifier opencv3.0 source (can be run directly), in face recognition field.
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基于opencv3.0的非线性SVM分类器源码(可直接运行),在人脸识别类的领域。-Based on nonlinear SVM classifier opencv3.0 source (can be run directly), in face recognition field.
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利用PCA算法进行特征提取和数据降维,再用SVM算法进行人脸识别的程序,里面有人脸数据库!-Use PCA algorithm for feature extraction and data reduction, and then SVM algorithm recognition program, which was face !
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SVM classifier for face recognition
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matlab代码实现人脸检测识别,提取人脸图像的kpca特征利用图像匹配快速识别人脸。-matlab face recognition kpca svm
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人脸特征提取与识别matlab程序,主要提取了PCA特征、SVM分类和核方法分类等,代码可以直接使用-Face recognition based on PCA features and Kernel methods, which is used in pattern extraction.
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利用LVQ神经网络对人脸朝向进行识别,并对比BP,SVM等算法-Using LVQ neural network for face recognition, and compared to SVM, BP algorithms
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图形界面的人脸识别代码,PCA+SVM多分类,yale图片库-Face recognition codes in GUI, PCA+SVM multi-classification, yale gallery
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人脸识别,分类SVM,对图片进行训练,标签,识别。-Face recognition, classification SVM
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是对jaffe人脸库进行识别测试的主程序,将jaffe人脸库分为训练集和测试集两部分,首先对图片进行LBP+LPQ特征提取,然后svm分类识别,统计识别率
-Is jaffe face recognition test the main library, the library will jaffe face divided into training and test sets of two parts, the first of LBP+LPQ image feature extrac
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最新SVM和PCA的人脸识别系统,详细地给出了用SVM解决问题的一般框架-Latest SVD and PCA Face Recognition System
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人脸识别系统采用了LBP PCA 2CKPCA 2BSVM算法实现的,效率高。-Face Recognition System using LBP PCA 2B KPCA 2B SVM algorithm, and high efficiency.
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这是基于pca与svm的人脸识别的GUI系统,自带ORL人脸库,亲测可以运行。-This is a GUI-based pca face recognition system with the svm, comes ORL , the pro-test can be run.
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PCA+svm算法进行人脸识别,识别率在百分之80~90-
Face recognition algorithm
Pca+ support vector machine
Recognition rate of about ninety percent, interested friends can be used as a reference
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相参脉冲串复调制信号,包括最小二乘法、SVM、神经网络、1_k近邻法,人脸识别中的光照处理方法。- Complex modulation coherent pulse train signal, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Face Recognition light treatment method.
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