Academic Thesis

Basic information

Name Iyono Atsushi
Belonging department
Occupation name
researchmap researcher code 1000229037
researchmap agency Okayama University of Science

Title

Recognitions of cosmic ray nuclear tracks in the GRAINE2018 emulsion films with machine learning approach

Bibliography Type

Joint Author

Author

A. Iyono, S. Akita, Y. Isayama, S. Yamamoto, F. Murakami, H. Rokujo,T. Nakano, S. Aoki, S. Takahashi, K. Kodama, S. Nagahara, M. Oda, T. Kato, K. Okamoto, M. Yamashita, S. Yoneno, M. Nakamura, O. Sato, K. Sugimura, Y. Nakamura, T. Nakamura, H. Minami, K. Namazawa and  on behalf of the GRAINE Collaboration

Summary

The GRAINE projects are going to perform the balloon flight with high angular resolution imaging technology by nuclear emulsion films, in April, 2023 at Alice Springs, Australia to explore the nature of gamma-ray emission of high energy stellar object such as Vela pulsar and the galactic center of milky way. The tracks of cosmic ray nuclei have already registered in the nuclear emulsion films exposed in the previous balloon flight of the GRAINE2018 project carried out at the Australia. The collection factor of cosmic ray nuclei in GRAINE2023 flight could be about 12 times larger than that of the GRAINE2018. We have been developing the image analysis application for track recognition of cosmic ray nuclei with a machine learning technology for the nuclear emulsion films. We are going to report the status of our approaches.

Magazine(name)

Proceedeings of Conference

Publisher

POS

Volume

Vol. 444

Number Of Pages

125

StartingPage

1

EndingPage

8

Date of Issue

2023/07

Referee

Not exist

Invited

Not exist

Language

English

Thesis Type

Research papers (proceedings of international meetings)

ISSN

DOI

DOI: https://doi.org/10.22323/1.444.0125

NAID

PMID

J-GLOBAL ID

arXiv ID

ORCID Put Code

DBLP ID