原文链接：http://blog.sina.com.cn/s/blog_6f7265cf0101o1jf.html
主要包括有OpenCV、Weka和Matlab，另外其中包含LibSVM、VlfeatepLearnToolbox等。
1、OpenCV
主页：http://opencv.org/ 下载地址：http://opencv.org/downloads.html 编程环境：VS 版本：2.4.8 教程：doc\opencv_tutorials.pdf API接口：doc\opencv2refman.pdf 特征检测： • "FAST" – FastFeatureDetector • "STAR" – StarFeatureDetector • "SIFT" – SIFT (nonfree module) • "SURF" – SURF (nonfree module) • "ORB" – ORB • "BRISK" – BRISK • "MSER" – MSER • "GFTT" – GoodFeaturesToTrackDetector • "HARRIS" – GoodFeaturesToTrackDetector with Harris detector enabled • "Dense" – DenseFeatureDetector • "SimpleBlob" – SimpleBlobDetector 描述符提取： • "SIFT" – SIFT • "SURF" – SURF • "BRIEF" – BriefDescriptorExtractor • "BRISK" – BRISK • "ORB" – ORB • "FREAK" – FREAK 机器学习： Normal Bayes Classifier K-Nearest Neighbors Support Vector Machines Decision Trees Boosting Gradient Boosted Trees Random Trees Extremely randomized trees Expectation Maximization Neural Networks kmeans
2、Weka 下载地址：http://www.cs.waikato.ac.nz/ml/weka/downloading.html LibSVM下载地址：http://www.csie.ntu.edu.tw/~cjlin/libsvm/ 编程环境：Eclipse 版本：3.6 教程：doc\index.html 机器学习： 1)weka.classifiers.bayes AODE AODEsr BayesianLogisticRegression BayesNet ComplementNaiveBayes DMNBtext HNB NaiveBayes NaiveBayesMultinomial NaiveBayesMultinomialUpdateable NaiveBayesSimple NaiveBayesUpdateable WAODE 2)weka.classifiers.functions GaussianProcesses IsotonicRegression LeastMedSq LibLINEAR LibSVM LinearRegression Logistic MultilayerPerceptron PaceRegression PLSClassifier RBFNetwork SimpleLinearRegression SimpleLogistic SMO SMOreg SPegasos VotedPerceptron Winnow 3)weka.classifiers.lazy IB1 IBk KStar LBR LWL 4)weka.classifiers.meta AdaBoostM1 AdditiveRegression AttributeSelectedClassifier Bagging ClassificationViaClustering ClassificationViaRegression CostSensitiveClassifier CVParameterSelection Dagging Decorate END FilteredClassifier Grading GridSearch LogitBoost MetaCost MultiBoostAB MultiClassClassifier MultiScheme OrdinalClassClassifier RacedIncrementalLogitBoost RandomCommittee RandomSubSpace RegressionByDiscretization RotationForest Stacking StackingC ThresholdSelector Vote 5)weka.classifiers.mi CitationKNN MDD MIBoost MIDD MIEMDD MILR MINND MIOptimalBall MISMO MISVM MIWrapper SimpleMI 6)weka.classifiers.rules ConjunctiveRule DecisionTable DecisionTableHashKey DTNB JRip M5Rules NNge OneR PART Prism Ridor Rule RuleStats ZeroR 7)weka.classifiers.trees ADTree BFTree DecisionStump FT Id3 J48 J48graft LADTree LMT M5P NBTree RandomForest RandomTree REPTree SimpleCart UserClassifier 8)weka.clusterers AbstractClusterer AbstractDensityBasedClusterer CheckClusterer CLOPE ClusterEvaluation Cobweb DBSCAN EM FarthestFirst FilteredClusterer HierarchicalClusterer MakeDensityBasedClusterer OPTICS RandomizableClusterer RandomizableDensityBasedClusterer RandomizableSingleClustererEnhancer sIB SimpleKMeans SingleClustererEnhancer XMeans
3、Matlab 主页：http://www.mathworks.cn/index.html 工具箱说明文档：http://www.mathworks.cn/products/index.html?sec=category 用途说明文档：http://www.mathworks.cn/discovery/?s_tid=brdcrb
1)DeepLearnToolbox工具箱 下载地址：https://github.com/yangzhixuan/DeepLearnToolbox 教程：看包含的示例程序 CNN SAE DBN CAE NN
2)Vlfeat工具箱 下载地址：http://www.vlfeat.org/download.html 视觉特征： HOG SIFT DSIFT LIOP MSER 机器学习： GMM K-means AIB Quick shift SLIC SVM Forests of kd-trees
3)Neural Network Toolbox工具箱 所有关于神经网络的开发
4)其他基本工具箱 特征检测： BRISK FAST Harris–Stephens minimum eigenvalue MSER SURF 描述符提取： extractFeatures HOG 分类/回归： Linear Regression Nonlinear Regression Generalized Linear Models Classification Trees and Regression Trees Discriminant Analysis Naive Bayes Classification Nearest Neighbors Model Building and Assessment 聚类： Hierarchical Clustering k-Means Clustering Gaussian Mixture Models Hidden Markov Models 集成： Boosting Bagging Random Subspace
