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76998

Classification of Corneal Pattern Based on Convolutional LSTM Neural Network

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Last updated: 25 Dec 2024

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Abstract

The development of the image classification techniques using deep learning has become one of the interesting research fields. It can be used in several fields such as the diagnosis of the corneal diseases. This paper proposes a Convolutional neural network – Long short-term memory (CNN-LSTM) model that can classifies the corneal images into normal and abnormal cases. The experimental results reveal that the CNN-LSTM neural network model provides a high performance. This model combines convolutional neural network (CNN) and long short-term memory (LSTM). The target of this combination is to extract complex features from the corneal images with a few number of layers rather than Convolutional neural networks. The proposed technique is carried out on a set of corneal images. These images are collected from patients via confocal microscopy.  The CNN-LSTM classification results on corneal fundus images achieved an accuracy of 100 %.  

DOI

10.21608/mjeer.2019.76998

Keywords

Deep learning, Convolutional neural network (CNN), Long short Term Memory (LSTM), Normal and abnormal corneal images and model accuracy

Authors

First Name

Nehad T.

Last Name

Haggag

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Affiliation

Department of Electronics and Electrical Communications EngineeringFaculty of Electronic Engineering Menoufia University: Menouf, Egypt.

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First Name

Ahmed

Last Name

Sedik

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Affiliation

Dep. of The Robotics and Intelligent Machines , Faculty of Artificial Intelligence, Kafrelsheikh University, Kafrelsheikh, Egypt

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First Name

Ghada M.

Last Name

Elbanby

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Dep. of Ind. Electronics and Control Eng., Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt

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First Name

Adel S.

Last Name

El-Fishawy

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Dept. of Electronics and electrical communication, Faculty of electronic Engineering, Menoufia University, Menouf, Egypt.

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First Name

Moawad I-

Last Name

Dessouky

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Dept. of Electronics and electrical communication, Faculty of electronic Engineering, Menoufia University, Menouf, Egypt.

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First Name

Ashraf A. M.

Last Name

Khalaf

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Affiliation

Department of Electronics and Electrical Communications Engineering Faculty of Engineering Minia University: Minia, EgyptCity, Country

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Volume

28

Article Issue

ICEEM2019-Special Issue

Related Issue

9704

Issue Date

2019-12-01

Receive Date

2020-03-11

Publish Date

2019-12-01

Page Start

158

Page End

162

Print ISSN

1687-1189

Online ISSN

2682-3535

Link

https://mjeer.journals.ekb.eg/article_76998.html

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https://mjeer.journals.ekb.eg/service?article_code=76998

Order

51

Type

Original Article

Type Code

1,088

Publication Type

Journal

Publication Title

Menoufia Journal of Electronic Engineering Research

Publication Link

https://mjeer.journals.ekb.eg/

MainTitle

Classification of Corneal Pattern Based on Convolutional LSTM Neural Network

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Article

Created At

22 Jan 2023