搜索资源列表
33754289
- 用MATLAB编写的svm源程序,可以实现支持向量机,用于特征分类或提取,(MATLAB prepared by the SVM source program, can realize the support vector machine (SVM), used for extracting feature classification or,)
基于图像的道路裂缝识别算法的研究
- 对于四种未修补裂缝分类问题，研究它们在方向以及分布密度上的差异性来进行裂缝类型 的划分。(For the problem of unrepaired crack classification, we use the differences of them on the crack direction and the distribution for crack classification. Using 2D feature mapping, Delaunay t
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- 基于SVM算法和纹理特征提取的遥感图像分类(based on the SVM algorithm and texture feature extraction of remote sensing image classification)
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- 基于底层特征和SVM的图像分类image classification based on the underlying characteristics and the SVM(image classification based on the underlying characteristics and the SVM)
C4_5
- C4.5算法，优秀的决策树算法，由于求解特征分类问题(C4.5 algorithm, an excellent decision tree algorithm, especially for the problem of feature classification)
案例1 BP神经网络的数据分类-语音特征信号分类
- 使用BP神经网络的数据分类-语音特征信号分类(Data classification using BP neural networks -- speech feature signal classification)
HOGFeature
- Hog特征提取，提取大量特征用于图像的分类识别(Hog Feature Extraction)
案例1 BP神经网络的数据分类-语音特征信号分类
- MATLAB神经网络案例分析 BP神经网络的数据分类-语音特征信号分类(MATLAB BP Neural Network - Classification of Speech Characteristic Signals)
finallyliuyuClassifier
- 用于文本分类，文本挖掘，文本特征提取，文本聚类，文本关联等(It is used for text classification, text mining, text feature extraction, text clustering, text association, etc.)
rfuncs
- 用随机森林的方法进行特征选择，对200了影像特征数据进行分类(Feature selection using random forest methods)
deepsae
- 构建深度sae网络，数据特征提取及分类，自定义网络结构参数(about deepsae code and an example, ex1 train a 100 hidden unit SDAE and use it to initialize a FFNN)
CSP
- CSP特征提取算法，可用于两类特征的数据分类中(CSP feature extraction algorithm)
test2-BP
- 采用BP神经网络设计男女生分类器。采用的特征包括身高、体重、是否喜欢数学、是否喜欢文学、是否喜欢运动共五个特征，BP神经网络包含一个隐层，隐层结点数为5。(Using BP neural network to design a classifier for male and female students. The features include height, weight, whether they like mathematics, whether they like literatur
libsvm-3.17
- 支持向量机，用于模式识别的特征分类，基于MATLAB的工具包(Support vector machines are used for feature classification of pattern recognition, based on MATLAB Toolkit)
SVM
- 通过HOG获取特征，用SVM对图像进行分类。(The feature is acquired by HOG, and the image is classified by SVM.)
cplst
- 多标签分类算法，通过对标签降维（SVD），然后利用线性回归建立特征和低维标签之间的关系，求出特征的系数，然后反过来进行预测(Multi label classification algorithm, through the tag dimension reduction (SVD), and then use linear regression to establish the relationship between features and low dimensional tags, to
svmtrain
- 基于支持向量机的对指定多个包含特征的训练集图片，包含label信息。训练后，可对于相同格式的图片进行分类。(A training set image containing multiple features is included in the support vector machine (SVM), which contains label information. After training, the pictures in the same format can be classifi
案例1
- BP神经网络的数据分配，对语言特征信号进行分类。(The data distribution of the BP neural network is used to classify the language characteristic signals.)
FeatureExtractionUsingAlexNetExample
- 本示例展示了怎样从一个预处理的卷积神经网络中提取特征，并用这些特征去训练一个图像分类器。(This example shows how to extract learned features from a pretrained convolutional neural network, and use those features to train an image classifier. Feature extraction is the easiest and fastest way use
audio_java
- python提取的乐器MFCC特征，调用TensorFlow 接口预测音频类别(Python extraction of the musical instrument MFCC features, calling the TensorFlow interface to predict the audio category)