Identification of High Energy Gamma Particles From the Cherenkov Gamma Telescope Data Using a Deep Learning Approach-Reference-Cited by-同舟云学术

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Identification of High Energy Gamma Particles From the Cherenkov Gamma Telescope Data Using a Deep Learning Approach

Published:2024 Issue: Volume:12 Page:16741-16752
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Karthick K.¹^ORCID,Agnes S. Akila²^ORCID,Kumar S. Sendil³^ORCID,Alfarhood Sultan⁴^ORCID,Safran Mejdl⁴^ORCID

Affiliation:

1. Department of Electrical and Electronics Engineering, GMR Institute of Technology, Rajam, Andhra Pradesh, India

2. Department of Computer Science and Engineering, GMR Institute of Technology, Rajam, Andhra Pradesh, India

3. Department of Electrical and Electronics Engineering, S. A. Engineering College (Autonomous), Chennai, India

4. Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

Funder

Researchers Supporting Project Number

King Saud University, Riyadh, Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10415380.pdf?arnumber=10415380

Reference41 articles.

1. Observation of TeV gamma rays from the Crab nebula using the atmospheric Cerenkov imaging technique

2. An Original Mechanism for the Acceleration of Ultra-High-Energy Cosmic Rays

3. Impact of Cosmic-Ray Physics on Dark Matter Indirect Searches

4. Gamma rays as probes of the Universe

5. A Review of Requirements for Gamma Radiation Detection in Space Using CubeSats

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