The 69th JSAP Spring Meeting 2022

Presentation information

Symposium (Oral)

Symposium » Machine learning in radiation research

[23p-F307-1~6] Machine learning in radiation research

Wed. Mar 23, 2022 1:00 PM - 4:15 PM F307 (F307)

Kenji Shinozaki(AIST), Ota Ryosuke(Hamamatsu Photonics )

3:45 PM - 4:15 PM

[23p-F307-6] Developments and applications of machine-learning technique to search for hypernuclear events

〇Manami Nakagawa1 (1.RIKEN)

Keywords:nuclei, machine learning

Particle and nuclear studies have been carried out using nuclear emulsion for a long time, and the nuclear emulsion with high positional resolution are still on of the most powerful detectors in this field.
However, a lot of time and effort is spent to analyze huge images.
So, in recent years, a machine learning technique has been introduced to efficiently detect traces in the images.
In this talk, I will introduce various machine learning methods used in hypernuclear study and present their applications.