Detecting Asteroids and Comets using Machine Learning and Deep Learning | ||||
MSA Engineering Journal | ||||
Volume 2, Issue 2 - Serial Number 6, March 2023, Page 967-972 PDF (479.37 K) | ||||
Document Type: Original Article | ||||
DOI: 10.21608/msaeng.2023.291924 | ||||
![]() | ||||
Authors | ||||
Mohamed Khalil![]() | ||||
1GSE department, Faculty of Engineering, October University for Modern Sciences and Arts (MSA), Giza, Egypt | ||||
2GSE Department, Faculty of engineering, MSA University | ||||
3Computer Engineering department, Faculty of engineering, MSA University | ||||
4Engineering MSA University. | ||||
5Mechatronics department, Faculty of engineering, MSA University | ||||
6Mechatronics Engineering department, Faculty of engineering, MSA University | ||||
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. | ||||
Keywords | ||||
Asteroids; Comets; Machine Learning; Deep learning | ||||
Statistics Article View: 127 PDF Download: 602 |
||||