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[Graph RecognizePCA+LDA.Class.vc

Description: 结合PCA+LDA的图像识别算法VC封装类,PCA(主元素分析,光照敏感),可用于人脸识别的初级算法-combination of image recognition algorithm VC Packaging category, PCA (principal component analysis, Light-sensitive), can be used for the initial face recognition algorithm
Platform: | Size: 3593 | Author: 郑翠花 | Hits:

[Other resourcepca

Description: 应用PCA(主成分分析)进行人脸识别的matlab程序,有较高成功率-PCA (Principal Component Analysis) face recognition Matlab procedures, which have a higher success rate
Platform: | Size: 1448 | Author: li | Hits:

[Special EffectsPixelFusion

Description: 利用vc实现图像的融合,包括一些经典的图像融合算法和主成分分析实现图像的融合.-use vc image fusion including some classic image fusion algorithms and principal component analysis image integration.
Platform: | Size: 5093507 | Author: 张素兰 | Hits:

[Other resourcePCA(matlab)

Description: 主成分分析算法(PCA),这是一个外国人编写的,很具有参考价值-principal component analysis algorithm (PCA), which was prepared by a foreigner, it is very valuable reference
Platform: | Size: 33277 | Author: 王超 | Hits:

[Special Effectspca

Description: 这是一个模式识别中关于主成分分析的特征提取的matlab源码-This is a pattern recognition on the Principal Component Analysis Feature Extraction of Matlab FOSS
Platform: | Size: 59698 | Author: fuali | Hits:

[GDI-Bitmapprincipal_components

Description: PCA = Principal Component Analysis PDF document. Learn it
Platform: | Size: 91008 | Author: selamicik | Hits:

[Other resourceIntroMatlab_codepls

Description: PCA and PLS aims:to get some insight into the bilinear factor models Principal Component Analysis (PCA) and Partial Least Squares (PLS) regression, focusing on the mathematics and numerical aspects rather than how s and why s of data analysis practice. For the latter part it is assumed (but not absolutely necessary) that the reader is already familiar with these methods. It also assumes you have had some preliminary experience with linear/matrix algebra.
Platform: | Size: 270941 | Author: 郭大 | Hits:

[Other resourceCoreJSP

Description: Core JSP In recent years, a large amount of software development activity has migrated from the client to the server. The client-centric model, in which a client executes complex programs to visualize and manipulate data, is no longer considered appropriate for the majority of enterprise applications. The principal reason is deployment—it is a significant hassle to deploy client programs onto a large number of desktops, and to redeploy them whenever the application changes. Instead, applications are redesigned to use a web browser as a \"terminal\". The application itself resides on the server, formatting data for the user as web pages and processing the responses that the user fills into web forms.
Platform: | Size: 1965127 | Author: gyzhen | Hits:

[Otherpalmprotected

Description: In the field of biometrics, palmprint is a novel but promising technology. Limited work has been reported on palmprint identification and verification, despite the importance of palmprint features. There are many unique features in a palmprint image that can be used for personal identification. Principal lines, wrinkles, ridges, minutiae points, singular points, and texture are regarded as useful features for palmprint representation.
Platform: | Size: 154321 | Author: Frankie | Hits:

[Audio programaudio_process_demo

Description: Garbe.Sound is a small .NET library for audio processing. The principal idea is to give programmers with a RAD environment for developing audio filters. With the basic classes, it comes with a few filters already implemented
Platform: | Size: 20786 | Author: 政逸 | Hits:

[WEB CodeATutorialonPrincipalComponentAnalysis

Description: A Tutorial on Principal Component Analysis.Principal component analysis (PCA) is a mainstay of modern data analysis - a black box that is widely used but poorly understood. The goal of this paper is to dispel the magic behind this black box.
Platform: | Size: 299986 | Author: viv | Hits:

[Other resourceppca

Description: Probabilistic Principal Components Analysis. [VAR, U, LAMBDA] = PPCA(X, PPCA_DIM) computes the principal % component subspace U of dimension PPCA_DIM using a centred covariance matrix X. The variable VAR contains the off-subspace variance (which is assumed to be spherical), while the vector LAMBDA contains the variances of each of the principal components. This is computed using the eigenvalue and eigenvector decomposition of X.
Platform: | Size: 1268 | Author: 西晃云 | Hits:

[Other resourcepca

Description: pca人脸识别This package implements basic Principal Component Analysis in Matlab and tests is with grayscale portion of the FERET database. Images are not preprocessed and it is up to the user to preprocess the images as wanted, not changing the filenames
Platform: | Size: 2636 | Author: 蔡加欣 | Hits:

[Other resourcetrainList

Description: PCA人脸识别 This package implements basic Principal Component Analysis in Matlab and tests is with grayscale portion of the FERET database. Images are not preprocessed and it is up to the user to preprocess the images as wanted, not changing the filenames
Platform: | Size: 3317 | Author: 蔡加欣 | Hits:

[Other resourceferet

Description: PCA人脸识别 This package implements basic Principal Component Analysis in Matlab and tests is with grayscale portion of the FERET database. Images are not preprocessed and it is up to the user to preprocess the images as wanted, not changing the filenames
Platform: | Size: 2353 | Author: 蔡加欣 | Hits:

[Other resourcefc

Description: PCA人脸识别 This package implements basic Principal Component Analysis in Matlab and tests is with grayscale portion of the FERET database. Images are not preprocessed and it is up to the user to preprocess the images as wanted, not changing the filenames
Platform: | Size: 967 | Author: 蔡加欣 | Hits:

[Other resourcecreateDistMat

Description: PCA人脸识别 This package implements basic Principal Component Analysis in Matlab and tests is with grayscale portion of the FERET database. Images are not preprocessed and it is up to the user to preprocess the images as wanted, not changing the filenames
Platform: | Size: 1480 | Author: 蔡加欣 | Hits:

[assembly language2Dcrystals

Description: Negative principal refractive indices and accidental isotropy in two-dimensional photonic crystals with an asymmetrical unit ce
Platform: | Size: 597059 | Author: Qtai | Hits:

[Other resourcepca

Description: matlab principal component analysis, PCA算法.
Platform: | Size: 1707 | Author: guodong | Hits:

[Other resourceprogmfc2

Description: The production of this book required the efforts of many people, but two in particular deserve to be singled out for their diligent, sustained, and unselfish efforts. Sally Stickney, the book s principal editor, navigated me through that minefield called the English language and contributed greatly to the book s readability. Marc Young, whose talents as a technical editor are nothing short of amazing, was relentless in tracking down bugs, testing sample code, and verifying facts. Sally, Marc: This book is immeasurably better because of you. Thanks.
Platform: | Size: 5461675 | Author: ch | Hits:
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