A Short Review on Machine Learning in Space Science and Exploration

Authors

DOI:

https://doi.org/10.61359/11.2106-2317

Keywords:

Machine Learning, Artificial Intelligence, Space Exploration, Space Science, Satellites and Rovers

Abstract

Machine learning is revolutionizing space exploration by tackling massive datasets, empowering astronauts, and driving scientific breakthroughs. From Deep Space 1's autonomous navigation to the James Webb Space Telescope's AI-assisted exoplanet discovery, Machine learning is transforming the present and shaping the future. With missions like NASA's Parker Solar Probe and the development of AI-powered monitoring systems and astro robots, the possibilities for unravelling the cosmos and democratizing space exploration are limitless. The future of space exploration lies in harnessing the power of ML to unlock the universe's secrets and make them accessible to all.

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Author Biography

Manas Biswal M, Department of Computer Science and Engineering, University College of Engineering Villupuram, Villupuram India - 605103

Manas Biswal M is an undergraduate researcher at University College of Engineering Villupuram, India, working in the Computer Science and Engineering Department. He is enthusiastic about integrating space science, exploration, and machine learning to provide novel solutions. The most recent work by Manas, "Review and Prospect of Machine Learning in Space Science and Exploration," explores how machine learning might be used to further space research. His enthusiasm for cutting-edge research reflects his commitment to solving problems at the nexus of space exploration and technology.

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Published

2023-12-25

How to Cite

Manas Biswal M. (2023). A Short Review on Machine Learning in Space Science and Exploration. Acceleron Aerospace Journal, 1(4), 84–87. https://doi.org/10.61359/11.2106-2317

Issue

Vol. 1 No. 4 (2023): The Cosmic Odyssey: A Voyage Through the Wonders of Aerospace and Space Research

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Articles

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License

Copyright (c) 2023 Manas Biswal M

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The Acceleron Aerospace Journal, with ISSN 2583-9942, uses the CC BY 4.0 International License. You're free to share and adapt its content, as long as you provide proper attribution to the original work.