ISSN2456-3315
Impact Factor10.57
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CrossRefDOI
ESTD2016
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AccessOpen
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Paper Title
Deep Learning in Exoplanet Detection: Enhancing Astronomical Discoveries
Authors
Daanveer Mehra
Keywords
Deep learning, exoplanet detection, astronomical discoveries, AI in space exploration, neural networks, telescope datasets, planetary signals, data analysis in astronomy.
Abstract
This research paper explores the metamorphic role of deep learning models in the detection of exoplanets in order for us to enhance our knowledge and understanding of this vast universe and perhaps even more and advance in astronomical discoveries. Deep Learning models display an evolutionary ability to distinguish planetary signals, an advancement I found quite favorable while comparing traditionally used methods with modern AI techniques. These findings provide us with a robust structure and framework for future explorations in planetary science.
This study delves deep into the role of deep learning in changing the field, leveraging sophisticated neural networks to analyze the intense amount of data from telescopes.
With this comparative analysis of classical methods, the findings emphasize the potential of AI in astronomical sciences, in this case, helping to discover exoplanets.
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How To Cite
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IJRTI — journal style
"Deep Learning in Exoplanet Detection: Enhancing Astronomical Discoveries", IJRTI - International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.10, Issue 1, page no.a928-a930, January-2025, Available :https://ijrti.org/papers/IJRTI2501112.pdf
APA — 7th edition
Mehra, D. (2025). Deep Learning in Exoplanet Detection: Enhancing Astronomical Discoveries. International Journal for Research Trends and Innovation, 10(1), a928-a930. https://ijrti.org/viewpaperforall.php?paper=IJRTI2501112
MLA — 9th edition
Mehra, Daanveer. "Deep Learning in Exoplanet Detection: Enhancing Astronomical Discoveries." International Journal for Research Trends and Innovation, vol. 10, no. 1, 2025, pp. a928-a930, https://ijrti.org/viewpaperforall.php?paper=IJRTI2501112.
Chicago — 17th, bibliography
Mehra, Daanveer. "Deep Learning in Exoplanet Detection: Enhancing Astronomical Discoveries." International Journal for Research Trends and Innovation 10, no. 1 (2025): a928-a930. https://ijrti.org/viewpaperforall.php?paper=IJRTI2501112.
Harvard — author–date
Mehra, D. (2025) 'Deep Learning in Exoplanet Detection: Enhancing Astronomical Discoveries', International Journal for Research Trends and Innovation, 10(1), pp. a928-a930. Available at: https://ijrti.org/viewpaperforall.php?paper=IJRTI2501112
IEEE — numbered reference
D. Mehra, "Deep Learning in Exoplanet Detection: Enhancing Astronomical Discoveries," IJRTI, vol. 10, no. 1, pp. a928-a930, Jan. 2025.
Vancouver — biomedical
Mehra D. Deep Learning in Exoplanet Detection: Enhancing Astronomical Discoveries. IJRTI. 2025 Jan;10(1):a928-a930.
AMA — 11th edition
Mehra D. Deep Learning in Exoplanet Detection: Enhancing Astronomical Discoveries. IJRTI. 2025;10(1):a928-a930. Accessed at https://ijrti.org/viewpaperforall.php?paper=IJRTI2501112
BibTeX — Zotero, Mendeley, LaTeX
@article{IJRTI2501112,
author = {Daanveer Mehra},
title = {Deep Learning in Exoplanet Detection: Enhancing Astronomical Discoveries},
journal = {International Journal for Research Trends and Innovation},
volume = {10},
number = {1},
pages = {a928-a930},
year = {2025},
month = {January},
issn = {2456-3315},
url = {https://ijrti.org/viewpaperforall.php?paper=IJRTI2501112}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Mehra, Daanveer
TI - Deep Learning in Exoplanet Detection: Enhancing Astronomical Discoveries
T2 - International Journal for Research Trends and Innovation
JA - IJRTI
VL - 10
IS - 1
PY - 2025
SN - 2456-3315
UR - https://ijrti.org/viewpaperforall.php?paper=IJRTI2501112
SP - a928-a930
ER -
Issue
Volume 10 Issue 1,
January-2025
Pages : a928-a930
Other Publication Details
Paper Reg. ID
IJRTI_200485
Published Paper ID
IJRTI2501112
Downloads
205,630
Research Area
Engineering
Country
-, -, India
Published
January 2025
Published Paper PDF
https://ijrti.org/papers/IJRTI2501112.pdf
Published Paper URL
https://ijrti.org/viewpaperforall.php?paper=IJRTI2501112
About Publisher
International Journal for Research Trends and Innovation
Published by IJRTI (JW Publication)
2456-3315
ISSN
10.57
Impact Factor
2016
ESTD Year
Open
Access
Impact Factor 10.57 calculated by Google Scholar and Semantic Scholar.
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Declarations
Funding
No external funding was received for this study.
Conflict of Interest
The authors declare that they have no conflict of interest.
Acknowledgements
The authors would like to thank the reviewers and the editorial board of International Journal for Research Trends and Innovation for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
