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291924

Detecting Asteroids and Comets using Machine Learning and Deep Learning

Article

Last updated: 05 Jan 2025

OverviewSimilar Items

Subjects

-

Tags

General Engineering

Abstract

 Asteroids and comets are potentially hazardous objects that may
make close approaches and enter into Earth's orbit. Detecting and
tracking asteroids and comets is a global challenge. Machine learning
and deep learning are powerful tools that can be used to observe such
hazardous objects early to protect our planet from any future impact.
In this paper, we attempt to present a concise review on using
machine learning and deep learning in tracking asteroids and comets.

DOI

10.21608/msaeng.2023.291924

Keywords

Asteroids, Comets, Machine Learning, Deep learning

Authors

First Name

Mohamed

Last Name

Khalil

MiddleName

-

Affiliation

GSE department, Faculty of Engineering, October University for Modern Sciences and Arts (MSA), Giza, Egypt

Email

mkibrahim@msa.edu.eg

City

-

Orcid

0000-0003-0634-4747

First Name

Mohamed

Last Name

Said

MiddleName

-

Affiliation

GSE Department, Faculty of engineering, MSA University

Email

msfahmy@msa.edu.eg

City

-

Orcid

-

First Name

Shahd

Last Name

El Sedfy

MiddleName

-

Affiliation

Computer Engineering department, Faculty of engineering, MSA University

Email

shahd.mustafa@msa.edu.eg

City

-

Orcid

-

First Name

Ahmed

Last Name

Ahmed

MiddleName

I.

Affiliation

Engineering MSA University.

Email

ahmed.ibrahim22@msa.edu.eg

City

-

Orcid

-

First Name

Mohamed

Last Name

Khaled

MiddleName

-

Affiliation

Mechatronics department, Faculty of engineering, MSA University

Email

mohamed.khaled50@msa.edu.eg

City

-

Orcid

-

First Name

Nada

Last Name

Abdellah

MiddleName

-

Affiliation

Mechatronics department, Faculty of engineering, MSA University

Email

naabdellah@msa.edu.eg

City

-

Orcid

-

First Name

Nada

Last Name

Khaled

MiddleName

-

Affiliation

Mechatronics Engineering department, Faculty of engineering, MSA University

Email

nada.farrag19@yahoo.com

City

-

Orcid

-

Volume

2

Article Issue

2

Related Issue

40382

Issue Date

2023-03-01

Receive Date

2023-03-23

Publish Date

2023-03-01

Page Start

967

Page End

972

Print ISSN

2812-5339

Online ISSN

2812-4928

Article File

MSAENG_Volume 2_Issue 2_Pages 967-972.pdf

PDF . 490.9kB

Link

https://msaeng.journals.ekb.eg/article_291924.html

Detail API

https://msaeng.journals.ekb.eg/service?article_code=291924

Order

291,924

Type

Original Article

Type Code

2,183

Publication Type

Journal

Publication Title

MSA Engineering Journal

Publication Link

https://msaeng.journals.ekb.eg/

MainTitle

Detecting Asteroids and Comets using Machine Learning and Deep Learning

Details

Type

Article

Created At

28 Dec 2024