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Classified_algorithm_of_image_pattern_identificati
- 提供VC下图像识别的分类算法,帮助初学者更好地进行图像识别学习.-provide VC Image Recognition under the classification algorithm, to help beginners to learn for image recognition.
maxminestimate
- 最大最小值估计,适合学习统计理论和模糊方面的结合应用,尤其是在模式识别方面的分类。-largest minimum estimate for statistical learning theory and fuzzy combination of the application, especially in regard to the classification of pattern recognition.
Classify
- VC实现的手写体识别程序。实现手写数字给出不同的分类器识别结果,可心采用模板匹配分类器(最邻近模板匹配法)识别, Bayes分类器识别(使用二值数据的Bayes方法,最小错误概率的Bayes方法,最小风险的Bayes方法),线性函数分类法识别(Fisher算法,奖惩算法,增量校正算法,LMSE算法的识别),非线性分类法(势函数法)识别,神经网络分类法识别(包括神经网络训练,神经网络建立后输出权值,测试与比较,神经网络识别)。 运行完全正确,是学习VC实现不同分类识别方法的很好代码。
sort
- 分类问题是利用已知类别的样品(训练集)来构造分类器,其训练集样品是已知类别的,所以又称为有监督学习。
meanshift
- 均值漂移测试程序,使用meanshift算法对随机产生的二维正态分布的随机数以及3D空间的数据进行聚类并绘图分步显示聚类过程,也可以从外部导入需要分类的数据,程序中有详尽的注释和说明,并且配有测试结果,非常适合计算机视觉、机器学习、模式识别的朋友参考-failed to translate
Bayes_classifier
- 贝叶斯分类器的设计实验,内有解释利于入门学习-Bayesian classifier design experiments, which help to explain the study entry
pca2D
- 一个基于pca2D的人脸识别分类程序, 并包含完整的FACE-ORL人脸库,很具有研究和学习价值-Pca2D based on face recognition classification procedures, and includes the complete FACE-ORL face database, it is with research and learning the value of
proj2.release
- 机器学习-人脸识别,根据给定的学习样例,提取特征,生成分类。对测试的样例进行人脸方向的分类。需要在vs中进行开发。-Machine learning- face recognition, according to the given learning sample, extract features, generate classification. The test sample to face the direction of classification. Vs the need to d
svm
- 选用支持向量机作为区分文本与非文本的分类器,支持向量机是在统计学习理论基础上发展起来的新一代学习算法,它在解决小样本、非线性及高维模式识别问题中表现出许多特有的优势。-Use support vector machine as the distinction between text and non-text classifier, support vector machine is in statistical learning theory developed on the basis of
AdaBoost_weaklearner_1
- adaboost 弱分类器学习算法,最成功的人脸识别算法。但是学习时间很长,这是它的缺点-adaboost
BagOfWords
- 基于Bag of word的图像分类经典文章,非常适合初学者学习-Bag of feature based classification
BagOfFeatureFramework
- 基于Bag of feature的图像分类经典文章,非常适合初学者学习-Bag of feature based classification
PMKBasedClassification
- 基于Pyramid Matching的图像分类经典文章,非常适合初学者学习-Pyramid matching based classification
SIFT_Global_Context
- 基于sift特征的的图像分类经典文章,非常适合初学者学习-SIFT based classification
ZhangJianGuo_Survey06
- Zhang Jianguo总结的图像分类检测算法对比经典文章,非常适合初学者学习-Survey of algorithms in classification and detection
patterndistinctive
- 模式识别经典书籍《模式分类》,让你更好的学习,模式识别-Pattern Recognition classic book " Pattern Classification" , allows you to better learning, pattern recognition! ! ! !
Pattern-Recognition-ppt
- 介绍模式识别的基本概念,详述了贝叶斯,参数估计,线性分类器,神经网络,随机方法,无监督学习与聚类等-Introduce the basic concepts of pattern recognition, Bayesian detailed, parameter estimation, linear classifiers, neural networks, stochastic methods, unsupervised learning and clustering, etc.
分类
- 图像分类,输出迭代学习次数与正确率的图像(Image classification, the output of iterative learning times and the correct rate of image)
kmeans图像分类
- 利用简单kmeans聚类算法,对不同图片进行分类,图片内容包括人像,风景,建筑,动物,植物等,平台是matlab。(The simple k - means clustering algorithm is used to classify different pictures. the picture content includes portrait, scenery, architecture, objects, plants, etc. The platform is MATLAB.)
svm支持向量机图像分类
- 通过支持向量机机器学习算法,实现对不同状态图像的分类,是非常好的方法。