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模式识别—分类程序VC源码,是《图像模式识别VC++技术实现》一书的源码-pattern recognition-classification procedure VC source, "VC image pattern recognition technology to achieve" a source book
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现有的代数特征的抽取方法绝大多数采用一维的方法,即首先将图像转换为一维向量,再用主分量分析(PCA),Fisher线性鉴别分析(LDA),Fisherfaces式核主分量分析(KPCA)等方法抽取特征,然后用适合的分类器分类。针对一维方法维数过高,计算量大,协方差矩阵常常是奇异矩阵等不足,提出了二维的图像特征抽取方法,计算量小,协方差矩阵一般是可逆的,且识别率较高。-existing algebra feature extraction method using a majority of th
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本程序实现了对一副图像中的材质不同的物体进行分类,对于材质相同的物体归为一类.-the realization of the image of a different material objects to the classification, For the same material objects classified as a category.
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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.
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MCA算法源程序,可用于稀疏分解,信号分类,图像修复,信号还原-MCA algorithm source code can be used for sparse decomposition, signal classification, image restoration, signal reduction
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最小错误概率贝叶斯分类器的matlab程序,可用于二维数据的分类以及分类效果的图像显示,可帮助初学者加深对贝叶斯分类算法的理解。-This is a matlab program of the minimum probability of error of Bayesian classifier.Which can display the image of two-dimensional data classification and the classification results . I
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一种基于图像像素分类的快速计算图像清晰度评价值函数。-Pixel classification based on image sharpness of the image evaluation value fast computing functions.
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利用感知机的线性分类功能,实现2维平面的两类模式分类,matlab实现,并用图像显示-Perceptron using linear classification function, the realization of 2-D plane of the two types of pattern classification, matlab achieve, and image display
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人工智能是现在科学发展的热门,该程序通过人工神经网络的原理实现图像的分类功能-The scientific development of artificial intelligence is now the most popular, the program adopted the principle of artificial neural network classification of image features
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基于Tensorflow下的cnn卷积神经网络实现图像的分类(Image classification CNN convolutional neural network based on Tensorflow)
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宽度学习是最近比较热的分类器,可用于图像分类等应用(image classification Broad learning)
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在CIFAR-10数据集上使用卷积神经网络进行图像分类(Image classification using convolution neural network on CIFAR-10 dataset)
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通过卷积网络,自动实现对图片特征的提取,通过训练,得到有效的权值,进行图像分类(Through convolution network, automatic extraction of image features can be realized. Through training, effective weights can be obtained and image classification can be carried out.)
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Locality-constrained Linear Coding (LLC) in place of the VQ coding in traditional SPM. LLC utilizes the locality constraints to project each descr iptor into its local-coordinate system, and the projected coordinates are integrated by max pooling to
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深度学习基本算法,深度学习with python作为标题建议介绍深度学习使用Python编程语言和开源Keras库,它允许简单快速的原型设计。
在Python深度学习中, 你将从一开始就学习深度学习,你将学习所有关于图像分类模型,如何使用深度学习获取文本和序列,甚至可以学习如何使用神经网络生成文本和图像。
本书是为那些具有Python技能的人员编写的,但你不必在机器学习,Tensorflow或Keras方面有过任何经验。你也不需要先进的数学背景,只有基础的高中水平数学应该让你跟随和理解核心
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以python语言为基础,利用tensorflow机器学习架构,两层卷积神经网络实现,CiFar数据集图片分类功能。(Based on Python language, using tensorflow machine learning architecture, two-layer convolutional neural network, CiFar data set image classification function.)
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支持向量机 MATLAB 源代码 图像分类(Support Vector Machine MatLAB Source Code Image Classification)
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BP神经网络,matlab程序编写,有原始数据,可用于遥感图像分类,并且对遥感图像的土地利用类型进行预测。(BP neural network, matlab programming, with original data, can be used for remote sensing image classification, and remote sensing image land use type prediction.)
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使用Matlab深度学习工具箱-googlenet 图像分类(Using GoogLeNet to classify images using deep learning toolbox)
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To classify four types of skin diseases such as Dermatitis, Melanoma, Diabetic foot ulcer, Impetigo,2 types of ML algorithms KNN and SVM are used. To get a visual representation of classifier output the ROC curve is plotted. To measure the performanc
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