Face and gender Recognition Using Genetic Algorithm and Hopfield Neural Network

Dr. C.R VIMAL CHAND

Face and gender Recognition Using Genetic Algorithm and Hopfield Neural Network

Dr. C.R VIMAL CHAND * §

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§ S.N.R Sons college

Face and gender Recognition Using Genetic Algorithm and Hopfield Neural Network

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Abstract

This paper describes a face recognition system for personal identification and verification using genetic algorithm and Hopfield Neural Network. This FRS system is also being trained for gender identification. Face recognition system consists of three steps. At the initial stage of this system some pre-processing are applied on the input image. Secondly, face features are extracted, which will be taken as the input of the eight parallel Hopfield neural network and genetic algorithm (GA). In the third step, classification is carried out by using Hopfield neural network and GA to identify gender. The proposed approaches can be tested on a number of face images. Sex-recognition in faces is a prototypical pattern recognition task and it appears to follow no simple algorithm. It is modifiable according to fashion (makeup, hair etc).While ambiguous cases exist, for which we must appeal to other cues such as physical build (if visible), voice pattern (if audible) and mannerisms.

References

12 Cites in Article

Reference Format

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr. CHAND. . "Face and gender Recognition Using Genetic Algorithm and Hopfield Neural Network". Global Journal of Computer Science and Technology GJCST Volume 10 (GJCST Volume 10 Issue 1).

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GJCST Volume 10 Issue 1

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

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Submission ReceivedFebruary 12, 2010
Peer Review Double Blind
Handling Editor
Accepted February 28, 2010
Published March 15, 2010

Version of record

v1.2

Issue date

July 10, 2010

Language

English

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Article Matrices

Total Score: 140

Country: Unknown

Subject: Global Journal of Computer Science and Technology

Authors: (PhD/Dr. count: 0)

View Count (all-time): 162

Total Views (Real + Logic): 5302

Total Downloads (simulated): 446

Publish Date: 2010 03, Mon

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Total Views: 5.3K

Total Downloads: 446

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