facial gender recognition using svm matlab code

Abstract

This paper presents a method for Gender Recognition using Support Vector Machine (SVM).This System
consists of two stages Feature Extraction and SVM Classification. In Feature Extraction we separate out eyes nose and mouth from the face. In SVM Classification those separated parts are grouped in two
parts.(Male anf Female). This System is carried out in two Process Training Process and Testing Process. In Training Process we create the database of few persons and mention their group ....etc

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Abstract
We investigate practical selection of meta-parameters for SVM regression (that is,
-insensitive zone and regularization parameter C). The proposed methodology advocates analytic
parameter selection directly from the training data, rather than resampling approaches commonly
used in SVM applications. Good generalization performance of the proposed parameter selection is
demonstrated empirically using several low-dimensional and high-dimensional regression
problems. Further, we point out the importance of Vapnik s -insens ....etc

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To get full information or details of iris recognition svm matlab code please have a look on the pages

http://seminarsprojects.net/Thread-synopsis-on-iris-recognition-using-matlab

if you again feel trouble on iris recognition svm matlab code please reply in that page and ask specific fields in iris recognition svm matlab code ....etc

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To get full information or details of detecting cancer part in medical images using svm please have a look on the pages

http://seminarsprojects.net/Thread-analysis-of-breast-cancer-using-image-processing-techniques-using-matlab

if you again feel trouble on detecting cancer part in medical images using svm please reply in that page and ask specific fields in detecting cancer part in medical images using svm ....etc

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I need fuzzy support vector machin matlab code, if any help me i would be mercifull. ....etc

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Human face contains a variety of information for adaptive social interactions amongst people. In fact, individuals are able to process a face in a variety of ways to categorize it by its identity, along with a number of other demographic characteristics, such as gender, ethnicity, and age. In particular, recognizing human gender is important since people respond differently according to gender. In addition, a successful gender classification approach can boost the performance of many other applications, including person recognition and smart hu ....etc

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matlab simulink OF dtc-svm five phases induction motor

ABSTRACT:This paper proposes design and simulation of a direct torque controlled induction motor drive system based on space vector modulation technique for ripple reduction.Direct Torque Control is a control technique used in AC drive systems to obtain high performance torque control. The principle is based on simultaneously decoupling the stator flux and electromagnetic torque. DTC drives utilizing hysteresis comparators suffer from high torque ripple and variable switching frequency.The ....etc

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filelist
psosvm
..\Examples
..\..\Classification
..\..\..\iris1v23.mat
..\..\..\iris2v13.mat
..\..\..\iris3v12.mat
..\..\..\linsep.mat
..\..\..\nlinsep.mat
..\..\Regression
..\..\..\example.mat
..\..\..\sinc.mat
..\..\..\titanium.mat
..\Optimiser
..\..\Makefile
..\..\ pr_loqo.c
..\..\ pr_loqo.h
..\..\ qp.c
..\..\qp.dll
..\best.mat
..\ binomial.m
..\cancer_input.mat
..\cancer_output.mat
..\ centrefig.m
..\ Classification_SVM_SteveGunn.asv
..\ Classification_SVM_SteveGunn.m
..\cmap.mat
..\ Contents.m
..\ fx.a ....etc

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code matlab algoritm pso svm

Abstract

The feature selection process can be considered a problem of global combinatorial optimization in machine learning, which reduces the number of features, removes irrelevant, noisy and redundant data, and results in an acceptable classification accuracy. Feature selection is of great importance in pattern classification, medical data processing, machine learning, and data mining applications. Therefore, a good feature selection method based on the number of features investigated for sample classification ....etc

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To get full information or details of svm code for offline signature verification in matlab please have a look on the pages

http://seminarsprojects.net/Thread-improved-offline-signature-verification-scheme-using-feature-point-extra-ction-method

http://seminarsprojects.net/Thread-signature-verification-code-using-matlab-fuzzy-logic

http://seminarsprojects.net/Thread-off-line-signature-verification-using-hmm-for-random-simple-and-skilled-forgeries

if you again feel trouble on svm code for offline signature verification in matlab please reply ....etc

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