글로벌 연구동향
방사선방호 및 안전
- 2023년 11월호
[Appl Radiat Isot .] Pulse height estimation and pulse shape discrimination in pile-up neutron and gamma ray signals from an organic scintillation detector using multi-task learning유기섬광검출기에서 누적 중성자, 감마선 신호 파고 및 파형 분석 연구KAERI, KAIST / 김준혁, 문명국*, 조규성*
- 출처
- Appl Radiat Isot .
- 등재일
- 2023 Sep:199:110880.
- 저널이슈번호
- 내용
Abstract
We developed a multi-tasking deep learning model for simultaneous pulse height estimation and pulse shape discrimination for pile-up n/γ signals. Compared with single-tasking models, our model showed better spectral correction performance with higher recall for neutrons. Further, it achieved more stable neutron counting with less signal loss and a lower error rate in the predicted gamma ray spectra. Our model can be applied to a dual radiation scintillation detector to discriminatively reconstruct each radiation spectrum for radioisotope identification and quantitative analysis.Affiliations
Junhyeok Kim 1, Byoungil Jeon 2, Jisung Hwang 1, Gyohyeok Song 1, Myungkook Moon 3, Gyuseong Cho 4
1Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
2Artificial Intelligence Application & Strategy Team, Korea Atomic Energy Research Institute, Daejeon, 34507, Republic of Korea.
3Neutron Science Division, Korea Atomic Energy Research Institute, Daejeon, 34507, Republic of Korea. Electronic address: moonmk@kaeri.re.kr.
4Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea. Electronic address: gscho@kaist.ac.kr.
- 키워드
- Deep learning; Multi-task learning; Organic scintillation detector; Pile-up; Pulse height estimation; Pulse shape discrimination.
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