搜索资源列表
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在matlab环境下实现的算法，该算法主要实现SVM分类的算法，svm入门-In the matlab environment to achieve algorithm to achieve SVM classification of the main algorithm, character recognition by SVM to achieve
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Matching Pursuit方法，经典的稀疏表示方法，可以用人脸识别和图像分类，图像去噪，现在非常流行。-Matching Pursuit method, sparse representation of the classic, you can use face recognition and image classification, image denoising, now very popular.
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提出一种基于分形理论和BP 神经网络的航空遥感图像有监督分类方法。该方法尝试将航空图像
的光谱信息和纹理特征相结合。它首先将彩色航空图像由RGB 格式转化为HSI 格式,然后,根据亮度计算分
数维、多重分形广义维数谱q-D( q) 和“空隙”等基于分形的纹理特征,同时加入归一化的色度和饱和度作为光
谱特征,采用BP 神经网络作为分类器。通过对彩色航空图像的分类实验,结果证实该方法行之有效。-Based on fractal theory and BP neural network
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论述了从搜索引擎上下载的动物图片的分类，识别方法-Discusses the search engine to download from animal picture classification, identification methods
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本文提出了一种新型的演进式学习的模型，可以通过自动下载网络上图片达到自动分类的目的-This paper presents a new evolutionary learning model, can automatically download the network picture to achieve the purpose of automatic classification
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在具有模式的完整统计知识条件下，按照贝叶斯决策理论进行设计的一种最优分类器。分类器是对每一个输入模式赋予一个类别名称的软件或硬件装置，而贝叶斯分类器是各种分类器中分类错误概率最小或者在预先给定代价的情况下平均风险最小的分类器。-In a model under the condition of complete statistical knowledge, in accordance with the Bayesian decision theory to design an optimal c
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利用bp神经网络对遥感图像进行分类，输入样本值后，根据样本值对遥感图像不同的地物进行分类，分类后计算每种地物所占面积-The use of bp neural network classification of remote sensing images, enter a sample value, based on the sample value of the different features of remote sensing image classification, classif
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KPCA与SVM共同用于人脸识别 SVM提高了分类效果 KPCA是一种借鉴SVM中核函数的一种较好的特征提取方法-KPCA and SVM for face recognition SVM together to improve the classification results from KPCA is a kernel function in SVM a better feature extraction method
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里面有了巧妙的方法提高了脑电信号分类准确性，有做EEG分类的可以看看。-There has been a clever way to improve the classification accuracy of EEG, and EEG classification can be done to see.
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这个PPT重点讲述SOM是什么，怎样运用SOM进行分类，是个不错的介绍，通过这一介绍可以使同学们对SOM有深刻的了解-The PPT focus on the SOM what is, and how to use SOM for classification, is a good introduction, through this presentation will enable students to have a deep understanding of the SOM
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his book is intended as a reference book for students, professionals and research
workers who need to apply statistical analysis to a large variety of practical
problems using STATISTICA, SPSS and MATLAB. The book chapters provide a
comprehe
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分类识别，可以选择很多方法，一般步骤：找特征点，训练，比对，找出方法
或者你的那种更容易，可以根据灰度值不同来查找具体位置-Classification, can choose to many methods and general steps: feature points, find training, comparison, find a way
Or the kind of easier, you can according to different gray values to
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应用Firsher线性判别器在matlab环境中实现模式识别的分类，简单直接，望采纳-Pattern recognition classification application Firsher linear discriminant in the Matlab environment is simple and direct, looking to adopt
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文本挡的firsher线性判别器是最简单的模式识别分类，在这里用了matlab进行了编程-Text the gear firsher linear discriminant is the most simple pattern recognition classification, where the Matlab programming
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适用于SIFT图像特征提取、K-means生成聚类、SVM图像分类-Image feature extraction, generation clustering, image classification
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介绍一个稳健性分析工具箱。主要做稳健性主成分、主成分回归、分类。-Our toolbox currently contains implementations of robust
methods for location and scale estimation, covariance estimation (FAST-MCD), regression (FAST-LTS, MCD-regression), principal
component analysis (RAPCA, ROB
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fault detection and classification
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基于神经网络的植物叶片分类识别 -Plant leaves Plant leaves classification based on neural network classification based on neural network
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提取灰度共生矩阵的分类作用，有利于后续的人工神经网络的进行-To extract the classification of the gray level co-occurrence matrix, is advantageous to the subsequent artificial neural network
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各种分类算法都包括在里面,有SVAR,ADMM等,在运用时,只需要调用就可以了。-Various classification algorithms are included in the inside, there SVAR, ADMM, etc., in the use, you only need to call on it.
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