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62514

FROM NEURAL NETWORK TO AIRCRAFT RECOGNITION SYSTEM

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Last updated: 04 Jan 2025

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Abstract

In this paper, an aircraft recognition system using a neural network is presented. A 2-D perspective view of aircraft models is first normalized through the preprocessing stage using bilinear interpolation and principal component analysis. The new patterns are invariant to translation, dilation, and rotation. Then, the Kohonen and Grossberg neural networks were trained using a small number of normalized patterns. The presented algorithm was tested on partially incomplete, noisy and geometrically distorted images and it was found that the recognition performance is 100% with six referenced aircraft.

DOI

10.21608/iceeng.1999.62514

Keywords

Image processing, Neural network, Pattern Recognition

Authors

First Name

A.

Last Name

Somaie

MiddleName

A.

Affiliation

R & D Centre, EAF Cairo

Email

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Orcid

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First Name

A.

Last Name

Badr

MiddleName

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Affiliation

Comp & Sys Eng. Dep., Faculty of Eng., Ain Shams University, Cairo

Email

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City

-

Orcid

-

First Name

T.

Last Name

Salah

MiddleName

-

Affiliation

R & D Centre, EAF Cairo

Email

-

City

-

Orcid

-

Volume

2

Article Issue

2nd International Conference on Electrical Engineering ICEENG 1999

Related Issue

9420

Issue Date

1999-11-01

Receive Date

2019-11-28

Publish Date

1999-11-01

Page Start

305

Page End

311

Print ISSN

2636-4433

Online ISSN

2636-4441

Article File

ICEENG_Volume 2_Issue 2nd International Conference on Electrical Engineering ICE….pdf

PDF . 1.3MB

Link

https://iceeng.journals.ekb.eg/article_62514.html

Detail API

https://iceeng.journals.ekb.eg/service?article_code=62514

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32

Type

Original Article

Type Code

833

Publication Type

Journal

Publication Title

The International Conference on Electrical Engineering

Publication Link

https://iceeng.journals.ekb.eg/

MainTitle

FROM NEURAL NETWORK TO AIRCRAFT RECOGNITION SYSTEM

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Article

Created At

22 Jan 2023