搜索资源列表
svm
- svm程序代码,用于模式识别和分类,也可用于图像特征。-svm code for pattern recognition and classification can also be used to image features.
SVM-KM
- 一个支持向量机的matlab工具箱,具有分类、拟合等功能,希望大家下载研学阿!-a Support Vector Machine Matlab toolbox, with classification, fitting features that you download Studies, A!
LS-SVMlab15aw.rar
- 这是一个很好的支持向量机的工具包,有回归、分类、寻优等功能。,This is a very good tool for support vector machine package, there is regression, classification, finding excellent features.
PedestrianExtraction
- 基于opencv的行人检测,用到了svm,haar特征-Opencv-based pedestrian detection, use the svm, haar features, etc.
MovingLeast-SquaresMLS
- 建立了一种基于移动最小二乘(Moving Least-Squares MLS)法的曲线曲 面拟合方法 这种方法对传统的最小二乘(LS)法的作了比较大的改进 使生成的曲线曲面具 有精度高 光滑性好等许多优点 详细介绍了移动最小二乘法的原理 应用和特点 并且给 出了使用移动最小二乘法进行曲线曲面拟合的程序设计流程 最后给出了曲线拟合和空间散 乱数据曲面拟合算例 将拟合结果与最小二乘拟合结果作了比较 分析了 MLS 拟合曲线曲 面的光滑性和拟合质量 表明了该方法的优越性和有效性-W
svm_face_recognition
- 一篇很不错的关于人脸表情识别的论文。论文提出了一种基于人脸局部特征的表情识别方法,先选取人脸重要的局部特征,对得到的局部特征进行主成分分析,然后用支持向量机( SVM)设计局部特征分类器来确定测试表情图像中局部特征,同时设计支持向量机( SVM)表情分类器,确定表情图像的所属类别。-A very good facial expression recognition on paper. This paper proposes a feature based on local expression
LS-SVM
- 主要叙述在matlab环境下熟悉对svm的操作以及svm的主要特性包括分类和回归-The main narrative in the matlab environment familiar with the operation of the SVM and the main features include SVM classification and regression
svml_v092
- SVM,很好用的用于模式识别中特征分类的咚咚。-SVM, a good use for pattern recognition features of the classification of咚咚.
bugtrack_aspt
- BugTrack is a basic, yet fully functional web based Bug Tracking system that you may use as a framework to create an expanded system or use as is . Great for small teams working on software projects. Features include: - Search by Project, Assi
libsvm-2.89
- 是一種線性方成的分類器。SVM透過統計的方式將雜亂的資料以NN的方式分成兩類,以便處理。LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM, and L1-loss linear SVM. -Main features of LIBLINEA
haar_wavelet_v4
- Haar-like features with SVM classification
svm-phasestateofcloudclassificationalgorithmsource
- 利用支持向量机的分类特性,结合modis的云图像,对云相态进行分类,利用svm云相态分类算法源代码-The use of support vector machine classification of features, combined with clouds modis images of the cloud phase state classification using svm-phase state of cloud classification algorithm source c
svm
- 很实用的一款svm工具箱,内包括很多的功能,且有详细的说明解释。 -A very useful svm toolbox includes many features, and a detailed descr iption of explanation.
Character-Recognition(Lib-SVM)
- 支持向量机的研究现已成为机器学习领域中的研究热点,其理论基础是Vapnik[3]等提出的统计学习理论。统计学习理论采用结构风险最小化准则,在最小化样本点误差的同时,缩小模型泛化误差的上界,即最小化模型的结构风险,从而提高了模型的泛化能力,这一优点在小样本学习中更为突出。SVM理论正是在这一基础上发展而来的,经过十几年的研究和发展,已开始逐步应用于一些领域。在解决小样本、非线性及高维模式识别问题中表现出许多特有的优势,已经在模式识别、函数逼近和概率密度估计等方面取得了良好的效果。- Support
SVM-based-image-classification
- 基于SVM的图像分类,由于支持向量机的分类能力极大地依赖于核参数的选取,因此,本文着重研究了核参数选择方法,并利用不同的颜色、纹理特征对图像进行分类。 -SVM-based image classification, the classification capability of SVM kernel parameters greatly depend on the selection, therefore, this paper focuses on the kernel paramet
Svm
- SVM实现图片分类,SIFT特征,可以自动读取文件下的图片和目录名(SVM realize picture classification, SIFT features, you can automatically read files under the pictures and directory names)
利用Hog特征和SVM分类器进行行人检测
- 利用Hog特征和SVM分类器进行行人检测(Using Hog features and SVM classifiers for pedestrian detection)
SVM
- 使用HOG提取特征,SVM进行图像分类,可以进行两种以上分类(Using HOG to extract features and SVM for image classification)
基于PCA和SVM的人脸识别系统
- 先通过图像处理提取人脸的各个特征,然后对人脸通过PCA进行降维,然后通过SVM进行人脸识别(Firstly, the features of human face are extracted by image processing, then the dimension of human face is reduced by PCA, and then the face is recognized by SVM)
改进svm
- phog方法提取图像特征,svm支持向量机进行分类,分别有GA遗传算法和PSO粒子群优化算法进行寻优。(Phog method extracted image features, SVM support vector machine classification, respectively, GA genetic algorithm and PSO particle swarm optimization algorithm for optimization.)