Detecting Asteroids and Comets using Machine Learning and Deep Learning

dc.contributor.author	Khalil Ibrahim, Mohamed
dc.contributor.author	Said, M.
dc.contributor.author	M. El-Sedfy, S.
dc.contributor.author	Khaled, M.
dc.contributor.author	Ibrahim, A.
dc.contributor.author	Abdellah, N. N. Khaled
dc.date.accessioned	2023-04-04T15:02:23Z
dc.date.available	2023-04-04T15:02:23Z
dc.date.issued	2023
dc.description.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.	en_US
dc.description.sponsorship	MSA University	en_US
dc.identifier.citation	Faculty of Engineering	en_US
dc.identifier.uri	http://repository.msa.edu.eg/xmlui/handle/123456789/5507
dc.language.iso	en	en_US
dc.publisher	October university for modern sciences and Arts MSA	en_US
dc.relation.ispartofseries	Faculty of Engineering;
dc.subject	Asteroids	en_US
dc.subject	Comets	en_US
dc.subject	Machine Learning	en_US
dc.subject	Deep learning	en_US
dc.subject	MSA University	en_US
dc.subject	October University of Modern Sciences And Arts	en_US
dc.title	Detecting Asteroids and Comets using Machine Learning and Deep Learning	en_US
dc.type	Article	en_US

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