Description: 我编写的基于颜色分量的汽车牌照定位识别。主要有以下几步：1 基于颜色分量的灰度值识别出车牌（基于蓝色车牌）2 从蓝色区域中识别白色的号码-prepared by the color components based on the vehicle license location identification. The following are the main steps : a component based on the color of gray values identification plates (based on blue plates) 2 from the blue and white identification numbers Platform: |
Size: 108544 |
Author:高锋 |
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Description: 基于ASM的人脸识别程序，包括训练部分。由Ghassan Hamarneh编写-ASM-based face recognition procedures, including the training component. Prepared by Ghassan Hamarneh Platform: |
Size: 23552 |
Author:ZhangGeng |
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Description: 统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含：
1，Analysis of linear discriminant function
2，Feature extraction: Linear Discriminant Analysis
3，Probability distribution estimation and clustering
4，Support Vector and other Kernel Machines-
This section should give the reader a quick overview of the methods implemented in
STPRtool.
• Analysis of linear discriminant function: Perceptron algorithm and multiclass
modification. Kozinec’s algorithm. Fisher Linear Discriminant. A collection
of known algorithms solving the Generalized Anderson’s Task.
• Feature extraction: Linear Discriminant Analysis. Principal Component Analysis
(PCA). Kernel PCA. Greedy Kernel PCA. Generalized Discriminant Analysis.
• Probability distribution estimation and clustering: Gaussian Mixture
Models. Expectation-Maximization algorithm. Minimax probability estimation.
K-means clustering.
• Support Vector and other Kernel Machines: Sequential Minimal Optimizer
(SMO). Matlab Optimization toolbox based algorithms. Interface to the
SVMlight software. Decomposition approaches to train the Multi-class SVM classifiers.
Multi-class BSVM formulation trained by Kozinec’s algorithm, Mitchell-
Demyanov-Molozenov algorithm Platform: |
Size: 4271104 |
Author:查日东 |
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Description: 从因子分析的角度出发解决基因表达谱分析问题。为解决独立成分分析方法在求解过程中的不稳定性，提出一种基于选择性独立成分分析的DNA微阵列数据集成分类器。首先对基因表达水平的重构误差进行分析，选择部分重构误差较小的独立成分进行样本重构，然后基于重构后的样本同时训练多个支持向量机基分类器，最后选择部分分类正确率较高的基分类器进行最大投票以得到最终结果。在3个常用测试集上验证了本文设计方法的有效性。-This paper tries to deal with gene expression problem in view of factor analysis. In order to overcome the instability problem caused by performing independent component analysis, a DNA microarray data ensemble classifier based on selective independent component analysis is proposed. The reconstruction error of each gene is analyzed firstly and a part of independent components which contribute relatively small reconstruction errors are selected to reconstruct new samples. After that, several support vector machine base classifiers are trained simultaneously. Finally, the best base classifiers with high correct rates are selected to participate in the ensemble, using the majority voting method. Results on three publicly available microarray datasets show the feasibility and validity of the method proposed in this paper. Platform: |
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Author:cumtgyy |
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Description: matlab处理指纹图像，由于指纹的唯一性、可靠性和稳定性，指纹已成为身份识别和鉴定的一个重
要标志，并被公认为“物证之首”。指纹识别作为一种生物识别技术，历来受到人们的广泛关注和重视，是未来个人身份认证的重要组成部分。-Fingerprint image processing matlab，Because the uniqueness of fingerprints, reliability and stability,fingerprint identification has become an important symbol of appraisal,and is recognized as the "first" material.The fingerprint identified as a kind of biometrics,has received extensive attention of,the individual identity authentication is the important component.Based on the MATLAB software applications for tools,for fingerprint image preprocessing and feature extraction technology research.Including pretreatment part involves by different methods of fingerprint image segmentation to extract valid area,with the improvement of OPTA thinning algorithm for thinning,
Platform: |
Size: 427008 |
Author:赖晓燕 |
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Description: 基于峭度极大的一种独立分量分析的算法，内有详细介绍每一步程序的作用和意义-Based on Kurtosis of a great independent component analysis algorithms, with detailed procedures for every step of the role and significance of Platform: |
Size: 1024 |
Author:高亚力 |
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Description: 使用Fuzzy Cluster Mean (FCM)與Principal component analysis (PCA)分類Yeast Data-Yeast data will be classified by means of Fuzzy Cluster Mean (FCM)and Principal component analysis (PCA) based on matlab. Platform: |
Size: 12288 |
Author:Peter |
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Description: A new approach toward target representation and localization, the central component in visual tracking of nonrigid objects,
is proposed. The feature histogram-based target representations are regularized by spatial masking with an isotropic kernel. The
masking induces spatially-smooth similarity functions suitable for gradient-based optimization, hence, the target localization problem
can be formulated using the basin of attraction of the local maxima. We employ a metric derived from the Bhattacharyya coefficient as
similarity measure, and use the mean shift procedure to perform the optimization. In the presented tracking examples, the new method
successfully coped with camera motion, partial occlusions, clutter, and target scale variations. Integration with motion filters and data
association techniques is also discussed. We describe only a few of the potential applications: exploitation of background information,
Kalman tracking using motion models, and face tracking. Platform: |
Size: 2459648 |
Author:Ali |
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Description: The multipath performance of a given signal/receiver combination depends on various signal and receiver parameters like signal type/modulation scheme pre correlation bandwidth and filter characteristics, chipping rate of code ,relative power levels of multipath signals ,chip spacing between correlators and type of discriminator used for tracking.
For the following analyses the influence of code multipath will be illustrated by means of multipath error envelopes.
In these diagrams, the resulting ranging errors are plotted as a function of geometric path delay .the computation of
multipath errors envelops is based on the assumption, that the direct signal component is always available and that only one
multipath signal is present-The multipath performance of a given signal/receiver combination depends on various signal and receiver parameters like signal type/modulation scheme pre correlation bandwidth and filter characteristics, chipping rate of code ,relative power levels of multipath signals ,chip spacing between correlators and type of discriminator used for tracking.
For the following analyses the influence of code multipath will be illustrated by means of multipath error envelopes.
In these diagrams, the resulting ranging errors are plotted as a function of geometric path delay .the computation of
multipath errors envelops is based on the assumption, that the direct signal component is always available and that only one
multipath signal is present Platform: |
Size: 5120 |
Author:Rafal |
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Description: Monochromatic (gray scale) low resolution image is converged to colored image by false color mapping to "hot" color scheme. This RGB image is then converted to Hue, Saturation and Value (HSV) image. Value component is replaced by higher resolution image and the resulting HSV image is converted back to RGB. This RGB merged image converted to gray scale is a merged image with improved spatial resolution. Platform: |
Size: 45056 |
Author:sofi |
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Description: 摘要：主成分分析（PCA）的人脸识别算法，以减少的特征向量是涉及到对抽象的特点，改进了主成分分析（一）iUumination算法的变化影响酶原sed.The方法是基于上减低与正常化其相应的标准差的特征向量元素相关联的大特征值的特征向量的影响力的想法。耶鲁大学和耶鲁大学面临的数据库面对数据库B是用来验证-Abstract：In principal component analysis(PCA)algorithms for face recognition，to reduce the influence of the
eigenvectors which relate to the changes of the iUumination on abstract features，a modified PCA ( A)
algorithm is propo sed．The method is based on the idea of reducing the influence of the eigenvectors associated
with the large eigenvalues by normalizing the feature vector element by its corresponding standard deviation．
Th e Yale face database and Yale face database B are used to verify the method．The simulation results show
that，f0r front face and even under the condition of limited variation in the facial po ses the proposed method
results in better perform ance than the conventional PCA and linear discriminant analysis(LDA)approaches．and
the computational cost remains the same as that ofthe PCA，and much less than that ofthe LDA． Platform: |
Size: 205824 |
Author:费富里 |
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Description: Kernel Entropy Component Analysis,KECA方法的作者R. Jenssen自己写的MATLAB代码，文章发表在2010年5月的IEEE TPAMI上面-Kernel Entropy Component Analysis, by R. Jenssen, published in IEEE TPAMI 2010.
We introduce kernel entropy component analysis (kernel ECA) as a new method for data transformation and dimensionality reduction. Kernel ECA reveals structure relating to the Renyi entropy of the input space data set, estimated via a kernel matrix using Parzen windowing. This is achieved by projections onto a subset of entropy preserving kernel principal component analysis (kernel PCA) axes. This subset does not need, in general, to correspond to the top eigenvalues of the kernel matrix, in contrast to the dimensionality reduction using kernel PCA. We show that kernel ECA may produce strikingly different transformed data sets compared to kernel PCA, with a distinct angle-based structure. A new spectral clustering algorithm utilizing this structure is developed with positive results. Furthermore, kernel ECA is shown to be an useful alternative for pattern denoising. Platform: |
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Author:johhnny |
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Description: One of Biometrics fields is face recognition & face expression recognition ...
1- In face recognition .. we need to design authentication program by training a neural network ,there are two source codes..one of them is based on Discrete Wavelet Transform with Perceptron Neural Network.. and the other based on Discrete Cosine Transform with Perceptron Neural Network ...
2- In face expression recognition .. we defined the condition of the person (nature,happiness,disgust or anger)
this source code is based on Principle component analysis(PCA) ..
* we need to now about digital image processing
,neural network and PCA-One of Biometrics fields is face recognition & face expression recognition ...
1- In face recognition .. we need to design authentication program by training a neural network ,there are two source codes..one of them is based on Discrete Wavelet Transform with Perceptron Neural Network.. and the other based on Discrete Cosine Transform with Perceptron Neural Network ...
2- In face expression recognition .. we defined the condition of the person (nature,happiness,disgust or anger)
this source code is based on Principle component analysis(PCA) ..
* we need to now about digital image processing
,neural network and PCA... Platform: |
Size: 11905024 |
Author:mahmoud |
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Description: 为实现合成孔径雷达（SAR）图像分类算法的测试与评估，将VC/Matlab 混合编程技术应用到SAR 图像分类平台开发中，分析与
比较了4 种VC/Matlab 混合编程方法及各自优缺点，并着重研究了基于组件对象模型（COM）的VC/Matlab 混合编程方法。使用Matlab
COM 编译器创建了SAR 图像分类算法组件，在VC 中调用其导出的接口函数。在此基础上，完成了SAR 图像分类平台的实例开发且
可脱离Matlab 环境运行。实验结果表明，该方法较好地发挥了VC 与Matlab 各自的优势，提高了SAR 图像分类平台开发的效率。-In order to test synthetic aperture radar （SAR） image classification algorithm，VC/Matlab mixed programming technology was
used in SAR image classification platform development. Four VC/Matlab mixed programming methods were introduced and analyzed.
Comparing with other three methods，the method based on component object model （COM） was studied particularly. SAR image
classification algorithm component was created by Matlab COM complier，and its interface function could be invocated with VC. Using this
method，a SAR image classification platform was realized. The platform could run without Matlab. The experimental result shows a good
combination of VC and Matlab. So，developing efficiency could be enhanced a lot. Platform: |
Size: 284672 |
Author:chengdu |
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Description: 基于负熵最大的独立分量分析，通过matlab代码，是本科毕设的题目，插值与拟合，解方程，数据分析，基于互功率谱的时延估计。- Based on negative entropy largest independent component analysis, By matlab code, The title of the commercial is undergraduate course you Interpolation and fitting, solution of equations, data analysis, Based on the time delay estimation of power spectrum. Platform: |
Size: 7168 |
Author:adatcmqka |
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Description: 仿真效率很高的，基于负熵最大的独立分量分析，通过matlab代码，是国外的成品模型，信号处理中的旋转不变子空间法，用于图像处理的独立分量分析，FMCW调频连续波雷达的测距测角。- High simulation efficiency, Based on negative entropy largest independent component analysis, By matlab code, Foreign model is finished, Signal Processing ESPRIT method, Independent component analysis for image processing, FMCW frequency modulated continuous wave radar range and angular measurements. Platform: |
Size: 10240 |
Author:wywkqj |
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Description: 仿真效率很高的，基于负熵最大的独立分量分析，通过matlab代码，是国外的成品模型，信号处理中的旋转不变子空间法，用于图像处理的独立分量分析，FMCW调频连续波雷达的测距测角。- High simulation efficiency, Based on negative entropy largest independent component analysis, By matlab code, Foreign model is finished, Signal Processing ESPRIT method, Independent component analysis for image processing, FMCW frequency modulated continuous wave radar range and angular measurements. Platform: |
Size: 9216 |
Author:wywkqj |
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Description: 数据模型归一化，模态振动，是一种双隐层反向传播神经网络，主同步信号PSS在时域上的相关仿真，最小均方误差（MMSE）的算法，在matlab R2009b调试通过，基于负熵最大的独立分量分析，通过matlab代码，包含收发两个客户端的链路级通信程序。- Normalized data model, modal vibration, Is a two hidden layer back propagation neural network, PSS primary synchronization signal in the time domain simulation related, Minimum mean square error (MMSE) algorithm, In matlab R2009b debugging through, Based on negative entropy largest independent component analysis, By matlab code, Contains two clients receive link-level communications program. Platform: |
Size: 8192 |
Author:mwdpxs |
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Search - component based by matlab